Scaled physical experiments using analog materials that simulate deformation processes in the Earth’s crust provide direct observations of deformation during strike-slip fault evolution. Carefully scaled experiments allow us to directly observe millions of years of deformation within hours and document the behavior of experimental faults. My thesis is composed of three distinct chapters that use scaled physical experiments to help us better understand partitioning of deformation on and off of strike-slip faults within the Earth’s crust. For my first project, I built a workflow that allows the measurement of off-fault deformation manifested as vertical motions along faults. When combined with horizontal displacements, these measurements allow us to quantify off-fault deformation in three dimensions during strike-slip fault experiments conducted in the geomechanics laboratory. My second project, inspired by the 2019 Ridgecrest earthquake, investigates the impact of pre-existing weaknesses during strike-slip fault evolution using scaled physical experiments with wet kaolin that simulate upper crustal deformation processes. Pre-existing weaknesses oriented 90-120˚ (counter-clockwise) from the primary fault experience left-lateral slip that matches co-seismic observations from the northern portion of the Ridgecrest main shock rupture. My third and final project utilizes results from experimental strike-slip faults on wet kaolin and dry sand (both poured and sedimented) to train convolutional neural networks (CNN) to predict off-fault deformation from maps of active strike-slip faults of different maturity such as those in southern California. The different analog materials produce different estimates of off-fault deformation along strike-slip faults due to the different portioning of strain on and off of faults within the materials. Whether due to material properties or active fault geometry, regions of greater off-fault deformation in the crust have greater shallow slip deficit so that surface estimates of deformation may underestimate sub-surface seismic hazard.