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Use this if you want to translate the research ranges into a rough body-weight estimate. If you are here for the article, the main takeaways start below.
Disclaimer: BMI cannot tell muscle from fat. Results depend heavily on your muscle massâtwo people at the same BMI can look completely different. Lifters and athletes often land in the "overweight" range while carrying low body fat. Use these numbers as rough population averages, not personal targets.
Health should always be prioritized over aesthetic numbers.
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Most Attractive Levels at a Glance
This page is organized around the practical takeaway: the facial and body-composition ranges that repeatedly score highest in attractiveness research. The study details are supporting evidence, not the main story.
Female face
BMI ~18-20
Face-morphing studies place peak female facial attractiveness around the lean-normal range.
Male face
BMI ~22-24
Male facial attractiveness tends to peak higher than female facial attractiveness.
Female body
Lean-normal
Female body-fat and BMI ratings generally move downward as fat mass rises within the studied range.
Male body
12-14% BF
Male physique ratings peak around a lean, athletic build rather than at the lowest possible body fat.
Female WHR
~0.7
Waist-to-hip ratio helps explain shape, but overall body fat and facial leanness are more central.
1. Facial Attractiveness: The Lean-Normal Range Scores Highest
The face is usually the first thing people judge. Across facial adiposity studies, attractiveness tends to peak in a normal-to-lean range: roughly 18-20 BMI for female faces and 22-24 BMI for male faces. Very high facial adiposity is consistently penalized, while extremely lean faces can also look worse than a healthy lean range.
Most Attractive Facial BMI by Study
Female face peaks cluster around ~18-20 BMI; male face peaks cluster around ~22-24 BMI.
Female Facial Body Fat Pattern
In morphing data, a slightly leaner-than-average face scored highest; both very lean and high-fat faces scored lower.
Useful takeaway: facial leanness helps until it starts looking unhealthy or gaunt.
Male and Female Patterns Side by Side
The most confusing part is that the female and male findings do not have the same shape. This comparison shows the core difference before the page goes into individual studies.
Wang et al. country average
Predicted attractiveness falls as BF% rises. Faint country lines appear in the detailed chart below.
Athletic-range peak
Male ratings rise into a lean athletic range and then decline, so âlowerâ is not always better.
2. Female Body Composition: Leaner Scores Higher in the Studied Range
The clearest body-level takeaway for women is simple: within the range studied by Wang et al. (2015), predicted attractiveness declined as body fat and BMI rose. This does not mean âas low as possibleâ; it means the most attractive range in this dataset sits on the lean-normal side.
Universal Trend
Countries showed a negative slope. Higher BF% = Lower Attractiveness.
Strongest Correlation
R² Value for Austria & Iran.
Equation (Austria): y = -0.1995x + 11.784
Female BF% vs Attractiveness (1â9 scale)
Model predictions from Wang et al. 2015 regression equations. All 10 rater countries shown.
Country-Level Evidence Strength
Countries Ranked by BF% R²
R² means âhow much of the rating pattern this metric explains.â Higher bars mean that countryâs attractiveness ratings tracked the selected body metric more strongly. Toggle metrics to compare BF%, BMI, and WHR.
BF% is very strong in Austria, Iran, Mauritius, and China; all 10 country slopes are negative.
3. Female Shape: The 0.7 WHR Signal
Waist-to-hip ratio is a shape cue, not the whole attractiveness formula. The useful takeaway is that a WHR around 0.7 repeatedly performs well for female figures, especially when paired with a healthy average-to-lean body composition.
Best simple shape marker: WHR around 0.7
This is most useful as a proportion signal. It should be read alongside facial leanness and overall body fat, not as a standalone score.
Supporting detail: Furnham et al. found average-weight figures with 0.7 WHR rated highest. Wang et al. found WHR weaker than BF% and BMI as a country-level predictor.
4. Male Bodies: Ratings Peak Around Athletic Builds
Male attractiveness does not simply rise as body fat gets lower. The strongest pattern is a lean, athletic middle: enough muscularity and shoulder width to look healthy, without drifting into either very thin or high-fat extremes.
The Male Sweet Spot
The practical target is not extreme leanness. The most attractive male range is closer to a visibly fit, athletic build: moderate-low body fat, healthy BMI, and a strong shoulder-to-waist ratio.
Optimal BMI
23â27
Optimal BF%
13-14%
Optimal SWR
1.57
Shoulder-to-Waist
Male Attractiveness vs Body Fat % (2025, UK/China/Lithuania)
Curve approximated from DEXA-based study; peak ~12â14% BF. Too lean or too fat both penalized.
Body composition is only half the picture
BMI and body fat shape perceptionâbut facial structure, symmetry, and harmony drive the first impression. Get your free AI facial attractiveness rating on Lookrank.
Free Facial Attractiveness RatingRelated Research
See how attractiveness scores are distributed globally, and how those ratings translate into real-world outcomes.
Edited by Alex Alstrom ¡ Questions: [email protected]