Patterns of object naming often differ between languages, but bilingual speakers develop convergent naming patterns in their two languages that are distinct from those of monolingual speakers of each language. This convergence appears to reflect dynamic interactions between lexical representations for the two languages. In this study, we present a self-organizing neural network model to simulate semantic convergence in the bilingual lexicon and investigate mechanisms underlying semantic convergence. Our results demonstrate that connections between two languages can be established through the simultaneous activations of related words in both languages, and these connections between two languages pull the two lexicons toward each other. These results suggest that connections between words in the bilingual lexicon play a major role in bilinguals’ semantic convergence. The model provides a foundation for exploring how various input variables will affect bilingual patterns of output.