This study introduces a sophisticated tire detection and prediction system that uses modern technology to enhance safety and maintenance quality. By anticipating fail and suggesting replace of current tire, the system promptly satisfies the demand for urgent tire care. Modern machine learning and image processing techniques are used by the system to enable real-time tire analysis and detection. The system’s scalable performance, robust back-end design, and good accuracy machine learning to make it appropriate for a variety of users, including everyday commuters and bikers. Given the significance of efficiency and safety, the system employs predictive methods to prolong the bicycle’s lifespan and avoid accidents brought on by tire failure. The goal of this research is to increase tire safety and dependability through maintenance suggestions. In the end, it establishes a new benchmark for upkeep and secure in the tire sector and signifies a substantial advancement in tire management.