Patellar tendinopathy is prevalent in sports requiring high jumping demands, and understanding the in vivo biomechanical behavior of the patellar tendon (PT) during landing is crucial for developing effective injury prevention and rehabilitation strategies. This study investigates the in vivo biomechanical behavior of the PT during the landing phase of a stop-jump task, integrating musculoskeletal modelling, finite element analysis (FEA), and a high-speed dual fluoroscopic imaging system (DFIS). A subject-specific knee joint model was constructed from CT, MRI, and dynamic X-ray data for a 27-year-old male (178 cm, 68 kg) at six time points during landing. Musculoskeletal simulations were used to estimated knee joint moments and quadriceps muscle forces, which were then applied to the finite element models. DFIS ensured accurate 3D spatial alignment of the models. Ridge regression analysis explored the relationship between applied biomechanical loads and the maximum equivalent (von Mises) stress in the PT. Maximum PT stress was observed at the bone attachment sites, with the highest stress (94.44 MPa) at initial ground contact, decreasing to a minimum of 16.37 MPa during landing. Regression analysis demonstrated a significant correlation (R² = 0.859, P < 0.001) between knee flexion moments, quadriceps muscle forces, and maximum PT stress, identifying these factors as key determinants of PT loading. This study underscores the importance of knee flexion moments and quadriceps muscle forces in influencing PT stress during landing. Future studies should include larger cohort to validate these results and explore the potential of machine learning for real-time injury risk prediction.