This newborn weight percentile calculator gives parents and clinicians a fast estimate of how a newborn's birth weight compares to peers of the same gestational age and sex, delivering a clear percentile, z-score, and benchmark weights.
Newborn Weight Percentile Calculator Inputs
Typical term newborns weigh between 2500 g and 4200 g.
Accepts 24 to 42 weeks; use decimal for days (e.g., 38.5).
Male
Female
Weight curves differ by sex because of body composition.
The newborn weight percentile calculator updates in real time and uses sex- and gestational-age-specific means and standard deviations to mirror clinical growth charts.
Chart shows gestational-age-specific 10th and 90th percentile bands with the newborn plotted as a red point.
Percentile Benchmarks by Gestational Age
Gestational Age (weeks)
10th Percentile (g)
50th Percentile (g)
90th Percentile (g)
Table recalculates percentile benchmarks for the selected sex using the same distribution assumptions as the newborn weight percentile calculator.
What is a newborn weight percentile calculator?
A newborn weight percentile calculator is a clinical decision aid that compares a baby's birth weight to standardized population data by gestational age and sex. Parents and clinicians use a newborn weight percentile calculator to confirm whether an infant is average for gestational age, small for gestational age, or large for gestational age, helping to guide monitoring and nutrition plans. A common misconception is that a newborn weight percentile calculator predicts future growth; instead, it only shows a snapshot relative to peers at birth.
Newborn weight percentile calculator Formula and Mathematical Explanation
The newborn weight percentile calculator relies on the z-score formula to translate birth weight into a percentile. The process starts with gestational-age-specific mean weight and standard deviation for the selected sex. The z-score is calculated as z = (actual weight − mean weight) divided by the standard deviation. The newborn weight percentile calculator then converts the z-score into a percentile using the cumulative normal distribution.
Step-by-step derivation for the newborn weight percentile calculator:
Choose the mean (μ) and standard deviation (σ) for the given gestational age and sex.
Compute z = (W − μ) / σ, where W is birth weight.
Apply the normal cumulative distribution to z to obtain Percentile = Φ(z) × 100.
Interpret: 50th percentile means the newborn is exactly average for that gestational age.
Variable
Meaning
Unit
Typical range
W
Birth weight entered into the newborn weight percentile calculator
grams
500–6000
μ
Mean weight for gestational age and sex
grams
600–3800
σ
Standard deviation of birth weight
grams
80–360
z
Z-score produced by the newborn weight percentile calculator
unitless
-3 to +3
Φ(z)
Cumulative normal probability
percent
0.1–99.9
Practical Examples (Real-World Use Cases)
Example 1: A 38.5-week female weighs 2900 g. The newborn weight percentile calculator finds a mean of about 3200 g and σ of 280 g. Z = (2900−3200)/280 = -1.07, percentile ≈ 14th. Clinically, this suggests monitoring for mild small-for-gestational-age risk and reinforcing feeding plans.
Example 2: A 40-week male weighs 4050 g. The newborn weight percentile calculator uses μ = 3650 g and σ = 330 g. Z = (4050−3650)/330 = 1.21, percentile ≈ 89th. This newborn weight percentile calculator result indicates a large-for-gestational-age infant, prompting glucose monitoring and anticipatory guidance.
How to Use This newborn weight percentile calculator
Enter birth weight in grams, select gestational age in weeks (decimals allowed), and choose sex. The newborn weight percentile calculator instantly returns percentile, mean, and z-score. Read the highlighted percentile: below 10th suggests small for gestational age, between 10th and 90th is average, and above 90th indicates large for gestational age. Use the newborn weight percentile calculator to decide whether to increase feeds, plan follow-up weight checks, or consider additional labs.
Key Factors That Affect newborn weight percentile calculator Results
Six key factors shape newborn weight percentile calculator outputs: gestational age accuracy, fetal growth velocity, maternal nutrition, placental health, genetics, and fluid status. Earlier gestations naturally lower expected weight, shifting the newborn weight percentile calculator outcome. Rapid third-trimester growth increases percentile, while placental insufficiency decreases it. Hydration and edema can temporarily raise weight, so the newborn weight percentile calculator should be paired with clinical judgment.
Financially, the newborn weight percentile calculator informs resource planning: small-for-gestational-age infants may need longer stays, impacting costs; large infants may require glucose monitoring; both scenarios influence discharge timing and follow-up billing.
Frequently Asked Questions (FAQ)
Does the newborn weight percentile calculator work for twins? It can be applied, but twins often follow different curves, so interpret cautiously.
What if gestational age is uncertain? The newborn weight percentile calculator loses precision; use best obstetric dating and re-evaluate clinically.
Is the newborn weight percentile calculator valid for preterm infants? Yes from 24 weeks onward, but neonatal teams may prefer specialized preterm curves.
Can I enter pounds instead of grams? Convert to grams first; the newborn weight percentile calculator requires grams for accuracy.
Why does sex change the result? Boys weigh slightly more on average, so the newborn weight percentile calculator uses sex-specific means.
What percentile is concerning? Below 10th or above 90th on the newborn weight percentile calculator warrants closer monitoring.
Does the calculator predict future obesity? No, the newborn weight percentile calculator reflects birth status only.
Can hydration skew the percentile? Transient fluid shifts can change weight by up to 5%, modestly affecting the newborn weight percentile calculator output.
Related Tools and Internal Resources
Growth percentile chart – Visual guide to compare your newborn weight percentile calculator result.
Fenton curve reference – Preterm benchmarks to pair with the newborn weight percentile calculator.
var dataPoints=[
{w:24,m:660,sdm:90,f:600,sdf:85},
{w:26,m:900,sdm:100,f:840,sdf:95},
{w:28,m:1200,sdm:120,f:1100,sdf:115},
{w:30,m:1600,sdm:150,f:1500,sdf:140},
{w:32,m:2100,sdm:180,f:2000,sdf:170},
{w:34,m:2600,sdm:220,f:2400,sdf:210},
{w:36,m:3000,sdm:260,f:2800,sdf:240},
{w:37,m:3200,sdm:280,f:3000,sdf:260},
{w:38,m:3400,sdm:300,f:3200,sdf:280},
{w:39,m:3550,sdm:320,f:3350,sdf:300},
{w:40,m:3650,sdm:330,f:3450,sdf:310},
{w:41,m:3720,sdm:340,f:3520,sdf:320},
{w:42,m:3780,sdm:350,f:3580,sdf:330}
];
function getStats(ga,sex){
var lower=dataPoints[0];
var upper=dataPoints[dataPoints.length-1];
for(var i=0;i<dataPoints.length;i++){
if(dataPoints[i].w=ga){upper=dataPoints[i];break;}
}
if(upper.w===lower.w){return buildStats(lower,sex);}
var ratio=(ga-lower.w)/(upper.w-lower.w);
var meanL=sex==="male"?lower.m:lower.f;
var meanU=sex==="male"?upper.m:upper.f;
var sdL=sex==="male"?lower.sdm:lower.sdf;
var sdU=sex==="male"?upper.sdm:upper.sdf;
var mean=meanL+(meanU-meanL)*ratio;
var sd=sdL+(sdU-sdL)*ratio;
return {mean:mean,sd:sd};
}
function buildStats(obj,sex){
return {mean:sex==="male"?obj.m:obj.f,sd:sex==="male"?obj.sdm:obj.sdf};
}
function normCdf(z){
var t=1/(1+0.2316419*Math.abs(z));
var d=0.3989423*Math.exp(-z*z/2);
var p=d*t*(0.3193815+t*(-0.3565638+t*(1.781478+t*(-1.821256+t*1.330274))));
if(z>0){p=1-p;}
return p;
}
function validateInputs(weight,ga){
var ok=true;
var errW="";
var errG="";
if(isNaN(weight)||weight<=0){errW="Enter a valid weight in grams.";ok=false;}
else if(weight6000){errW="Weight should be between 400 g and 6000 g.";}
if(isNaN(ga)||ga<=0){errG="Enter gestational age in weeks.";ok=false;}
else if(ga42){errG="Gestational age must be 24–42 weeks.";}
document.getElementById("errWeight").innerHTML=errW;
document.getElementById("errGest").innerHTML=errG;
document.getElementById("errSex").innerHTML="";
return ok;
}
function updateCalc(){
var weight=parseFloat(document.getElementById("weightGrams").value);
var ga=parseFloat(document.getElementById("gestAge").value);
var sex=document.getElementById("sex").value;
if(!validateInputs(weight,ga)){return;}
var stats=getStats(ga,sex);
var mean=stats.mean;
var sd=stats.sd;
var z=(weight-mean)/sd;
var perc=Math.max(0,Math.min(99.9,normCdf(z)*100));
var p10=mean-1.28*sd;
var p90=mean+1.28*sd;
document.getElementById("mainResult").innerHTML="Estimated percentile: "+perc.toFixed(1)+"th";
document.getElementById("meanResult").innerHTML="Expected mean weight: "+Math.round(mean)+" g";
document.getElementById("sdResult").innerHTML="Standard deviation: "+Math.round(sd)+" g";
document.getElementById("zResult").innerHTML="Z-score: "+z.toFixed(2);
document.getElementById("rangeResult").innerHTML="Approximate 10th to 90th range: "+Math.round(p10)+" g to "+Math.round(p90)+" g";
document.getElementById("formulaNote").innerHTML="Formula: z = (weight − mean) / SD; Percentile = NORMCDF(z). This newborn weight percentile calculator uses sex- and gestational-age-specific μ and σ.";
updateTable(sex);
drawChart(weight,ga,sex);
}
function resetCalc(){
document.getElementById("weightGrams").value=3200;
document.getElementById("gestAge").value=40;
document.getElementById("sex").value="male";
document.getElementById("errWeight").innerHTML="";
document.getElementById("errGest").innerHTML="";
document.getElementById("errSex").innerHTML="";
updateCalc();
}
function copyResults(){
var text=document.getElementById("mainResult").innerText+"\n"+document.getElementById("meanResult").innerText+"\n"+document.getElementById("sdResult").innerText+"\n"+document.getElementById("zResult").innerText+"\n"+document.getElementById("rangeResult").innerText+"\nAssumptions: Sex-specific normal distribution by gestational age.";
navigator.clipboard.writeText(text);
}
function updateTable(sex){
var tbody=document.getElementById("benchTable");
var html="";
for(var i=0;i<dataPoints.length;i++){
var mean=sex==="male"?dataPoints[i].m:dataPoints[i].f;
var sd=sex==="male"?dataPoints[i].sdm:dataPoints[i].sdf;
var p10=Math.round(mean-1.28*sd);
var p50=Math.round(mean);
var p90=Math.round(mean+1.28*sd);
html+="
"+dataPoints[i].w+"
"+p10+"
"+p50+"
"+p90+"
";
}
tbody.innerHTML=html;
}
function drawChart(weight,ga,sex){
var canvas=document.getElementById("chart");
var ctx=canvas.getContext("2d");
ctx.clearRect(0,0,canvas.width,canvas.height);
var padding=40;
var w=canvas.width – padding*2;
var h=canvas.height – padding*2;
var minW=500;
var maxW=4000;
for(var i=0;imaxW){maxW=mVal+300;}
}
ctx.strokeStyle="#cfd8e3″;
ctx.lineWidth=1;
for(var j=0;j<=4;j++){
var y=padding+h*(j/4);
ctx.beginPath();
ctx.moveTo(padding,y);
ctx.lineTo(padding+w,y);
ctx.stroke();
}
function scaleX(week){
var minGa=24;
var maxGa=42;
return padding + ( (week – minGa) / (maxGa – minGa) ) * w;
}
function scaleY(val){
var ratio=(val – minW)/(maxW – minW);
return padding + h – ratio*h;
}
function drawLine(series,color){
ctx.strokeStyle=color;
ctx.lineWidth=2;
ctx.beginPath();
for(var i=0;i<dataPoints.length;i++){
var mean=sex==="male"?dataPoints[i].m:dataPoints[i].f;
var sd=sex==="male"?dataPoints[i].sdm:dataPoints[i].sdf;
var val=series===10?mean-1.28*sd:mean+1.28*sd;
var x=scaleX(dataPoints[i].w);
var y=scaleY(val);
if(i===0){ctx.moveTo(x,y);}else{ctx.lineTo(x,y);}
}
ctx.stroke();
}
drawLine(10,"#004a99");
drawLine(90,"#28a745");
ctx.fillStyle="#c00";
var xPt=scaleX(ga);
var yPt=scaleY(weight);
ctx.beginPath();
ctx.arc(xPt,yPt,5,0,Math.PI*2);
ctx.fill();
ctx.fillStyle="#004a99";
ctx.font="12px Arial";
ctx.fillText("Weight",xPt+8,yPt-4);
ctx.fillText("Weeks",canvas.width/2,canvas.height-padding/3);
ctx.save();
ctx.translate(14,canvas.height/2);
ctx.rotate(-Math.PI/2);
ctx.fillText("Weight (g)",0,0);
ctx.restore();
}
updateCalc();