In this study, controlling a bidirectional DC/DC converter using a model predictive controller is examined. The preferred bidirectional converter is designed to be used in powertrains of electric and hybrid vehicles. Thanks to the use of bidirectional converters in these vehicles, the performance of the battery pack increases, while the range limit of the vehicle is relatively increased with regenerative braking. On the other hand, bidirectional converters play a key role to benefit from integrated charging systems. For all these functionalities mentioned, not including any system in addition to the existing topology ensures the best use of the limited space in the vehicle. Considering the non-linear characteristics of both the battery and the electric motor, the use of classical linear controllers adversely affects the system performance. For this reason, controllers that explicitly consider the optimization problem are widely preferred today. Model predictive controllers are evaluated in this context. In the study, the state-space model of the converter was first created. After that, the switched model of the system was prepared in the MATLAB/Simulink environment and the system was controlled with a model predictive controller. The controller was designed using rapid prototyping techniques. In the simulation, the performance of the controller is examined for both cases by changing the power flow direction.