Despite advances in care of tetralogy of Fallot (ToF) patients, there is still limited understanding of which patients will experience adverse RV remodeling and subsequent clinical events. ToF patients’ cardiac function is often assessed using cardiovascular magnetic resonance (CMR) imaging, which provides excellent views of the right heart. However, manual analysis of these images is time-consuming and variable. Additionally, CMR provides data enabling quantification of pulmonary artery (PA) hemodynamics, but has not been investigated in association with outcomes in post-repair ToF patients (rToF). Computational fluid dynamics (CFD) simulations could provide insight into factors affecting right ventricular (RV) remodeling. There remains an unmet need to identify features that characterize and predict progression from repair to RV remodeling and outcomes. My objectives in this dissertation were to identify the structural and hemodynamic parameters of rToF that associated with RV remodeling in order to improve both clinical care and quality of life. I approached this objective using two specific aims. In Aim 1, I developed a supervised machine learning algorithm to automatically segment cardiac volumes using CMR images. This algorithm enabled robust and repeatable measurements of cardiac structure and function for both cross-sectional and longitudinal analyses. In Aim 2, I created patient-specific PA models to study geometry and hemodynamics. From Aim 1, I found that RV dV/dt (volumetric rate of change) was associated with risk of pulmonic valve replacement (PVR), while several left-sided metrics were associated with RV end-diastolic volume index rate of change. From Aim 2, I found that wall shear stress in the left and right PAs, as well as oscillatory shear index (OSI) in the main PA, was associated with risk of PVR. I also found that left PA OSI was associated with RV end-systolic volume index rate of change. In conclusion, I identified multiple novel predictors for PVR as well as factors associated with RV remodeling. It is my hope that these methods can be applied and validated in larger cohorts to enable studies that will support physicians and researchers in their understanding and treatment of rToF, leading to improved care and outcomes for these patients.