A statistical model of facial attractiveness

Christopher P. Said, Alexander Todorov

Research output: Contribution to journalArticlepeer-review

106 Scopus citations


Previous research has identified facial averageness and sexual dimorphism as important factors in facial attractiveness. The averageness and sexual dimorphism accounts provide important first steps in understanding what makes faces attractive, and should be valued for their parsimony. However, we show that they explain relatively little of the variance in facial attractiveness, particularly for male faces. As an alternative to these accounts, we built a regression model that defines attractiveness as a function of a face's position in a multidimensional face space. The model provides much more predictive power than the averageness and sexual dimorphism accounts and reveals previously unreported components of attractiveness. The model shows that averageness is attractive in some dimensions but not in others and resolves previous contradictory reports about the effects of sexual dimorphism on the attractiveness of male faces.

Original languageEnglish (US)
Pages (from-to)1183-1190
Number of pages8
JournalPsychological Science
Issue number9
StatePublished - Sep 2011

All Science Journal Classification (ASJC) codes

  • General Psychology


  • attractiveness
  • face


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