Both development and progression of knee osteoarthritis have been associated with the loading of the knee joint during walking. We are, therefore, interested in developing strategies for changing walking biomechanics to offload the knee joint without resorting to surgery. In this study, simulations of human walking were performed using a 2D bipedal forward dynamics model. A simulation generated by minimizing the metabolic cost of transport (CoT) resembled data measured from normal human walking. Three simulations targeted at minimizing the peak axial knee joint contact force instead of the CoT reduced the peak force by 12–25% and increased the CoT by 11–14%. The strategies used by the simulations were (1) reduction in gastrocnemius muscle force, (2) avoidance of knee flexion during stance, and (3) reduced stride length. Reduced gastrocnemius force resulted from a combination of changes in activation and changes in the gastrocnemius contractile component kinematics. The simulations that reduced the peak contact force avoided flexing the knee during stance when knee motion was unrestricted and adopted a shorter stride length when the simulated knee motion was penalized if it deviated from the measured human knee motion. A higher metabolic cost in an offloading gait would be detrimental for covering a long distance without fatigue but beneficial for exercise and weight loss. The predicted changes in the peak axial knee joint contact force from the simulations were consistent with estimates of the joint contact force in a human subject who emulated the predicted kinematics. The results demonstrate the potential of using muscle-actuated forward dynamics simulations to predict novel joint offloading interventions.