In this project we study the correlation between symmetry and attractiveness of faces through statistical pattern recognition and neural networks. We design an intelligent agent that learns to use a given set of standards to distinguish between beautiful and ordinary faces: We represent the faces as feature vectors in a vector space in order to measure the degree of symmetry. To implement a larger data set, we use 2-dimensional wavelet representation to improve the performance.