A chemical recycling process that reduces polymers to their raw materials plays a crucial role in circular economy. To contribute to chemical recycling, this study proposes a system that simulates the process of depolymerization from polymer-to-monomer using reactive molecular dynamics (MD). Two MD methods, Reax force field (ReaxFF) and neural network potential (NNP), were employed to simulate the depolymerization of a polystyrene model. We validated the simulation accuracies by comparing monomer yields and decomposition products with experimental results. The results showed that NNP-MD accurately replicated the degradation and redecomposition processes and achieved consistency with the experimental data at various temperatures. ReaxFF-MD, however, was less able to represent the depolymerization process. We conclude that NNP-MD is capable of simulating polymer depolymerization results that are consistent with experimental observations. These results contribute to the development of methods for efficient chemical recycling and the broader realization of a circular economy.