Cycling, a sport embraced by enthusiasts ranging from casual riders to competitive athletes, demands personalized training plans for performance enhancement. This project presents an innovative data-driven methodology that harnesses historical Strava activity data to craft individualized cycling training plans. Our system executes a two-step data mining pipeline, integrating ride data clustering and personalized plan classification. The resulting tailored plans cater to individual cyclist needs, obviating the necessity for personal coaching. This research contributes a scalable and accessible solution to the realm of personalized training plans, serving a diverse spectrum of cyclists seeking performance optimization.