The cost and time efficiency of computational wear simulations may enable the optimization of total knee replacements for the reduction of polyethylene wear, thereby potentially improving the long term success of total knee replacements. However, previously existing computational wear models have only demonstrated weak correlations (R²<0.65) in comparison to knee simulator wear tests. This thesis presents the development and verification of new computational models for the simulation of polyethylene wear in total knee replacements. Finite element and multibody dynamic simulation models were implemented for the prediction of total knee replacement contact mechanics. A new wear model was developed, based on a time dependent cross shear and energy dissipation approach, and was evaluated for the prediction of total knee replacement wear. The effects of contact pressure on polyethylene wear were investigated through both computational and in vitro experiments. This verified computational wear model was further advanced through the development and addition of a lubrication model, which provided consideration for the colloidal protein mediated boundary lubrication of total knee replacements. Finally, the predictability of the newly developed computational model was evaluated through the prediction of a broad range of pin-on-disk and knee simulator wear test experiments. The time dependent – energy dissipation – colloidal boundary lubrication model developed in this thesis resulted in greatly improved correlation strength for the prediction of pin-on-disk (R²=0.85) and knee simulator wear test (R²=0.96) results compared with previously published wear models such as Archard’s wear law (R²=0.12), time independent cross shear wear models (R²=0.60) and other time dependent wear models (R²=0.65). The computational wear simulation models developed in this thesis have demonstrated sufficient predictive accuracy (Validation Metric:​ 0.85) to enable the optimization of total knee replacements for the reduction of wear, which may improve the long term success of these necessary clinical devices.