Ensemble perception, the extraction of a statistical summary of multiple instances of a feature, enables efficient processing of information. Here we investigated whether ensemble representations can be formed for facial attractiveness, a socially important complex feature. After verifying that our face stimuli produced by geometric morphing represented a valid continuum of attractiveness (Experiment 1), we asked participants to compare the average attractiveness of four faces with a single probe face. Whether the four faces were homogeneous or heterogeneous resulted in highly similar performance levels, suggesting the visual system could extract an ensemble representation of the attractiveness of a heterogeneous group of faces. Statistical simulations with human-level bias and noise indicated participants did not rely on subsampling one random face or the most/least attractive face from the array (Experiment 2). Ensemble perception of facial attractiveness was not affected by variance in the stimulus array (Experiment 3), did not depend on memory of individual faces in the array (Experiment 4), and could be extended to larger arrays with faces asymmetrically distributed around the set mean (Experiment 5). Our findings give further evidence to the prevalence of perception of statistical regularities in vision.