A new method called mean-shift Mallows model average (MSA) estimator has been developed to combine different models' estimates. This estimator improves upon existing methods by controlling for location bias and regression error simultaneously. The MSA estimator is shown to be better than the Mallows model average (MMA) estimator in terms of accuracy. Simulation results demonstrate that the MSA estimator consistently outperforms the MMA estimator.