Mitral regurgitation is the most frequent valve disease in patients over the age of 65 years. In patients with high surgical risk, transcatheter mitral valve intervention (TMVI) is the preferred therapy. However, patient selection for this therapy remains a challenge. This study aims at developing a simulation tool to assist surgeons pre-operatively to choose the treatment based on the patient’s characteristics. In this study, a clinical data (echocardiography and CT scans) of a TMV recipient with a history of severe mitral calcification was considered. Left ventricular (LV) and mitral valve (MV) models were obtained from pre-TMVI CT scans. Pre- and post-TMVI hemodynamics were generated by a lumped-parameter model which were then applied as boundary conditions for two fluid–structure interaction (FSI) simulations with contractile LV and dynamic MV; first, a pre-TMVI simulation with the anatomical MV model and second, a post-TMVI simulation with a Tendyne transcatheter mitral valve model. Mitral pressure gradients (MPG) and effective orifice area (EOA) were calculated. The predictions of the pre-TMVI simulations closely resembled Echo data. Calcified mitral leaflets led to a narrowing of the diastolic opening area resulting in an increased pressure gradient over the MV; EOA (FSI: 2.1 cm2, ECHO: 1.9 cm2), MPG (FSI: 3.8 mmHg, ECHO: 3.4mmHg). These values improved significantly for the post-TMVI simulation (EOA: 4.5 cm2, MPG: 1.1 mmHg), Figure 1. By combining medical imaging and computer modeling, we established a validated tool that can be used pre-TMVI to assist clinicians to select the optimal therapy based on patients’ characteristics.Figure 1. Pre-, and post-TMVI simulation of a patient with severely calcified mitral valve; TMVI: transcatheter mitral valve intervention