Modeling of friction stir welding (FSW) is challenging, as there are large gradients in both strain rate and temperature that must be accounted for in the constitutive law of the material being joined. Constitutive laws are most often calibrated using flow stresses from hot compression or hot torsion testing, where strain rates are much lower than those of the FSW process. As such, the current work employed a recently developed method to measure flow stresses in AA 2219-T67 at the high strain rates typical of FSW. These data were used in the development of a finite element simulation of FSW to study the effect of the new flow stress data on temperature, torque, and load predictions, compared to standard material models calibrated with hot compression or hot torsion data. It was found that load predictions were significantly better with the new material law, reducing the error with respect to experimental measurements by approximately 79%. Because heat generation during FSW is primarily a function of friction between the rapidly spinning tool and the workpiece, the choice of friction law, and associated parameters, were also studied with respect to FE model predictions. It was found that the Norton (viscoplastic) friction law was the most appropriate for modeling FSW, because its predictions were more accurate for both the transient and steady-state phases of the FSW plunge experiment. The postulated reason for the superior performance of the Norton law was its ability to account for temperature and rate sensitivity of the workpiece material sheared by the tool, while the Tresca limited Coulomb law favored contact pressure, with essentially no temperature or rate dependence of local material properties. The combination of the new flow stress data and the optimized Norton friction law resulted in a 63% overall reduction in model error, compared to the use of a standard material law and boilerplate friction parameters. The overall error was calculated as an equally weighted comparison of temperatures, torques, and forces with experimentally measured values.