Mitral valve regurgitation is the most common valvular disease, affecting 10% of the population over 75 years old. Left untreated, patients with mitral valve regurgitation can suffer declining cardiac health until cardiac failure and death. Mitral valve repair is generally preferred over valve replacement. However, there is a direct correlation between the volume of cases performed and surgical outcomes, therefore there is a demand for the ability of surgeons to practice repairs on patient specific models in advance of surgery, however, producing a mesh model of the valve geometry from TEE imaging remains a challenge. We have developed a 3D Slicer module incorporating DeepMitral to enable fully automated mitral valve leaflet segmentations. From leaflet segmentations, we can extract the atrial surface and generate a positive mold of the patient-specific leaflet geometry. These molds can then be 3D printed to be used in the production of dynamic silicone valve models for functional simulation in our beating heart phantom, enabling various repair techniques to be evaluated prior to surgery. Our 3D Slicer module simplifies the overall workflow for valve modelling by automating previously manual steps and incorporating them into a single user interface. We demonstrate an algorithm for extracting the atrial surface from an automatic leaflet segmentation, enabling creation of a positive mold mesh that can easily be 3D printed. By simplifying the modelling workflow, we aim to improve the clinical translatability of patient-specific heart valve modelling.