Agent-based simulation holds significant potential for advancing research in team cognition. However, developing models that can accurately reflect and align with real-world team dynamics poses considerable challenges. This paper presents our approach to designing a simulation model that integrates Transactive Memory Systems (TMS) into the Mutual Belief Model, effectively capturing and analyzing team dynamics. Starting from a conceptual framework, we designed a task suitable for both real-life and simulated environments; conducted experiments; and collected findings that serve as evidence to validate the model’s mechanisms through empirical experimentation. Our preliminary findings indicate that the integrated model effectively captures key aspects of team dynamics, such as information sharing and expertise recognition. This method can ensure that our model is not only theoretically sound but also empirically supported, enhancing its applicability and accuracy in studying team behaviors. By bridging TMS with the Mutual Belief Model, our study provides a novel framework for understanding and simulating complex team interactions, offering the potential for more accurate and scalable research in team cognition.