Facial babyishness has a strong impact on social perceptions and interactions; however, the components constituting a babyface remain unclear. In this paper, we present a computational approach for identifying important but less apparent facial patterns of a babyface, using voluminous face images on the web. The proposed approach is built upon computationally efficient data mining techniques. A new image set with ground truth data collected from users and an evaluation approach based on age estimation are presented in the experiment. The results show that the mined patterns are effective for understanding and determining babyfaces. The findings of this study should provide information for future investigations on the prediction and analysis of trait impressions using the patterns.