The swift increase in the adoption of electric vehicles (EVs) has necessitated the enhancement of campus microgrids’ hosting capacity to meet the rising demand for charging while ensuring system stability and efficiency are not compromised. This research introduces an innovative method utilizing the Marine Predators Algorithm (MPA) to optimize the hosting capacity for EVs within campus microgrids. The MPA, which draws inspiration from the hunting techniques of marine predators, provides a robust solution to the intricate and nonlinear challenges associated with load management, renewable energy integration, and overall grid performance. The proposed approach reduces power losses, enhances voltage stability, and guarantees system reliability by optimizing the distribution of distributed energy resources (DERs) and coordinating EV charging schedules. Simulation outcomes indicate that the MPA surpasses traditional optimization techniques in achieving greater hosting capacity while adhering to system constraints. This study underscores the promise of bio-inspired algorithms as a sustainable and efficient means to facilitate the integration of EVs into contemporary microgrids, thereby contributing to the development of smarter and more environmentally friendly energy systems.