What role can computational modeling play in psychology? What are the main advantages of instantiating theories as computer simulations? How should one assess the value of a given model? In this paper, our goals are to introduce and to discuss these issues. We argue for an essentially utilitarian view of computational modeling. We suggest that the main function of computational modeling is to support an interactive process of “probing and prediction” through which models can be interacted with in a way that provides both guidance for empirical research and also sufficient depth to support interactive modification of the underlying theory. We propose that models, just as the systems they are models of, can only be understood land evaluated) with respect to a given level of description and a specific set of criteria associated with that level. We also claim that models gain explanatory power as well as practical usefulness when they are emergent, that is, when they provide an account of how the principles of organization at a given level of description constrain and define structure at a higher level of description. For this reason, connectionist models appear to provide the most fruitful modeling framework today.