The Online Bike Rental System is a web-based platform designed to improve traditional bike rental services by addressing issues such as manual booking, limited accessibility, and inefficient inventory management. It provides a streamlined interface where users can search, book, and manage bike rentals, while administrators can oversee inventory and reservations efficiently. To enhance user experience, the system incorporates a cosine similarity algorithm that analyzes user browsing behavior and recommends bikes with similar features to previously viewed options. This personalized recommendation approach improves accuracy in suggestions, increases user satisfaction, and optimizes the overall booking process. The project demonstrates how data-driven algorithms can enhance efficiency and personalization in rental services.