Computational heart models successfully predicted how left ventricular assist devices (LVADs) would affect six women with peripartum cardiomyopathy, a severe heart condition occurring around childbirth. The simulations showed ejection fraction improvements varied dramatically based on disease severity, with more severely affected patients experiencing greater benefits from mechanical support. In patients with the lowest heart function, the LVAD became the sole source of blood pumping. This represents a significant advance in personalized cardiovascular medicine, potentially transforming treatment decisions for women facing life-threatening heart failure during or after pregnancy. Traditional trial-and-error approaches to LVAD settings could be replaced with patient-specific modeling that predicts optimal pump speeds before implantation. The technology addresses a critical gap since peripartum cardiomyopathy affects roughly 1 in 2,000 pregnancies and can be fatal without prompt intervention. However, this preprint study requires peer review validation, and the findings are based on computer simulations rather than actual clinical outcomes. While promising for reducing maternal mortality, real-world validation studies comparing predicted versus actual LVAD responses will be essential before clinical implementation.