The present study focuses on optimizing the internal transportation fleet of a Peruvian university using a linear programming model to adjust the size of the fleet. Through a quantitative and descriptive approach, user data was collected at 10 stops for 30 days, where a linear programming mathematical model was applied to optimize the size of the internal transport fleet, the solution of which was achieved through the use of the Solver add-on Excel. The results indicated that the optimal fleet is 2 units, which improves transportation planning and management, providing a more effective and satisfactory service. The research highlights the need for formal optimization methods to address university-level mobility problems. It demonstrates that route optimization can significantly reduce congestion and improve operational efficiency, contributing to a more sustainable and efficient transport service.