A computational model of language learning is a formal description of how linguistic input can be transformed into either mental representations or (linguistic) behavior. For instance, a model may formally describe how a speech signal directed at a child can be processed to learn word-meaning mappings, a problem all human children face. In addition, the model may outline how this leads to subsequent behavioral responses such as looking or pointing at a referent. As they implement formal algorithms, computational models of language learning are theoretical proposals of the mental representations and processes underlying human language acquisition. Although a computational model can refer to any detailed specification of such a cognitive process, most modern computational models are computer programs that implement (some aspect of) language learning. These implementations allow simulation of the linguistic behavior or its developmental trajectory and systematic comparison of the model to that of a human language learner. Such a comparison allows the researcher to assess the success of the underlying theoretical account in explaining empirical findings or observations regarding the linguistic process under study and to facilitate deriving theoretical predictions that may have not yet been empirically investigated.