Rheumatic heart disease (RHD) is a neglected tropical disease despite the substantial global health burden. In this study, we aimed to develop a lower cost method of modeling aortic blood flow using subject-specific velocity profiles, aiding our understanding of RHD's consequences on the structure and function of the ascending aorta. Echocardiography and cardiovascular magnetic resonance (CMR) are often used for diagnosis, including valve dysfunction assessments. However, there is a need to further characterize aortic valve lesions to improve treatment options and timing for patients, while using accessible and affordable imaging strategies. Here, we simulated effects of RHD aortic valve lesions on the aorta using computational fluid dynamics (CFD). We hypothesized that inlet velocity distribution and wall shear stress (WSS) will differ between RHD and non-RHD individuals, as well as between subject-specific and standard Womersley velocity profiles. Phase-contrast CMR data from South Africa of six RHD subjects with aortic stenosis and/or regurgitation and six matched controls were used to estimate subject-specific velocity inlet profiles and the mean velocity for Womersley profiles. Our findings were twofold. First, we found WSS in subject-specific RHD was significantly higher (p < 0.05) than control subject simulations, while Womersley simulation groups did not differ. Second, evaluating spatial velocity differences () between simulation types revealed that simulations of RHD had significantly higher than non-RHD (p < 0.05), these results highlight the need for implementing subject-specific input into RHD CFD, which we demonstrate how to accomplish through accessible methods.