This article reviews a particular computational modeling approach to the study of psychological development--that of constructive neural networks. This approach is applied to a variety of developmental domains and issues, including Piagetian tasks, shift learning, language acquisition, number comparison, habituation of visual attention, concept learning, and theory of mind. Implications of this modeling for theoretical understanding of psychological development are considered. (Contains 9 figures.)