Surface fault rupture displacements are a primary hazard that must be avoided or accommodated in our engineering infrastructure. Recent research in this field has indicated the potential for using material point method modeling to gain a better understanding of the displacement predictors. This study aims to use fault box lab testing data to calibrate material point method modeling, and then explore an expanded range of predictor variable values. The physical experiments were conducted in making a 2.2 m long and 0.7 m wide fault box with a depth of soil of 0.8 m. The fault box was constructed in a way that simulates reverse fault rupture at 30°, 45°, and 60°. For each test, the same cohesionless Monterey sand was used. Three tests were performed in the fault box propagating displacement through loose, loose over dense, and dense samples. The loose samples were created using dry pluviation. The dense samples were created using vibro-densification. Before each test was conducted, the shear wave velocity was measured by embedding two accelerometers in the sand at a fixed distance and providing a source of shear waves at the sample surface. As the tests were conducted, two cameras filmed the process of creating the surface fault rupture, one from the top view and one from a side view showing the shear band as it propagated to the surface. The displacement was measured using a displacement potentiometer. This fault box data was then used for calibrating the Anura3D framework for material point method modeling. Utilizing the same boundary conditions and soil parameters, all tests conducted in the fault box were modeled and replicated in the software. Once calibrated to the experiments the numerical modeling was then used to explore more complex sample layering, different dip angles, and the addition of inclusions or hard spots within the samples. The results of this numerical exploration will be presented at the time of the workshop.