We propose a model of social cognitive development based not on a single modeling framework or the hypothesis that a single model accounts for children’s developing social cognition. Rather, we advocate a Causal Model approach (cf. Waldmann, 1996), in which models of social cognitive development take the same position as theories of social cognitive development, in that they generate novel empirical hypotheses. We describe this approach and present three examples across various aspects of social cognitive development. Our first example focuses on children’s understanding of pretense and involves only considering assumptions made by a computational framework. The second example focuses on children’s learning from “testimony”. It uses a modeling framework based on Markov random fields as a computational description of a set of empirical phenomena, and then tests a prediction of that description. The third example considers infants’ generalization of action learned from imitation. Here, we use a modified version of the Rational Model of Categorization to explain children’s inferences. Taken together, these examples suggest that research in social cognitive development can be assisted by considering how computational modeling can lead researchers towards testing novel hypotheses.