Osteoarthritis (OA) is a debilitating disease that leads to disability and loss of quality of life. Post-traumatic osteoarthritis (PTOA) is a version of OA that develops after acute injury to the knee. PTOA is of particular interest because the disease can manifest earlier in life compared to primary OA. Several studies have shown that changes in the mechanical properties of soft tissues in the knee (articulating cartilage and menisci) are associated with worsening OA grades. Changes to the tissue mechanical properties must be considered to generate realistic computational models of individuals who have suffered traumatic injuries to the knee. Therefore, we developed a method to non-invasively estimate subject-specific articular cartilage material properties by utilizing magnetic resonance imaging (MRI). High-resolution MR images were acquired of one subject’s knee joint before compression (uncompressed scan) and then after compression of the knee joint’s articular cartilage (compressed scan). The compression was performed by a MRIloading device, which applied a load equal to half the subject’s body weight to the plantar aspect of the foot. Hexahedral meshes were created from the subject’s knee joint soft tissues in the uncompressed scan. The boundary conditions of the model were set to mimic the conditions in the MR-scanner:​ half the subject’s body weight applied to the tibia along its long axis, and the femur was fixed in all degrees of freedom. The thickness of the subject’s tibiofemoral articular cartilage tissues, as determined from the compressed MR scan, were used as a target for a Gauss-Newton optimization. FE simulations were performed iteratively with updated parameters after every iteration until the approximate tissue thickness of the compressed scan was observed, requiring 53 iterations (total of 85 hours runtime) to converge at a 0.5% tissue thickness difference between simulated results and the compressed MR-scan. The material parameter results from our simulation fall within the range of literature values, which allows us to conclude that the methodology developed during this study is reliable and produces subject-specific parameters of knee joint articular cartilage. In future work we will apply the modeling framework developed in this study to patients after traumatic injury, with the goal of improving understanding of early mechanical changes in the joint alter the probability that patient develops PTOA.