This manuscript surveys computational modeling efforts by researchers in developmental psychology. Developmental psychology is ready to blossom into a modern science that focuses on causal mechanistic explanations of development rather than just describing and classifying behaviors. Computational modeling is the key to this process. However, to be effective, models must not only mimic observed data. They must also be transparent, grounded, and plausible to be accepted by the developmental psychology community. Connectionist model provides one such example. Many developmental features of typical and atypical perception, cognition, and language have been modeled using connectionist methods. Successful models are closely tied to the details of existing empirical studies and make concrete testable predictions. The success of such a project relies on the close collaboration of computational scientists with empirical psychologists