Blood flow patterns in the human left ventricle (LV) have shown relation to cardiac health. However, most studies in the literature are limited to a few patients and results are hard to generalize. This study aims to provide a new framework to generate more generalized insights into LV blood flow as a function of changes in anatomy and wall motion. In this framework, we studied the four-dimensional blood flow in LV via computational fluid dynamics (CFD) in conjunction with a statistical shape model (SSM), built from segmented LV shapes of 150 subjects. We validated results in an in-vitro dynamic phantom via time-resolved optical particle image velocimetry (PIV) measurements. This combination of CFD and the SSM may be useful for systematically assessing blood flow patterns in the LV as a function of varying anatomy and has the potential to provide valuable data for diagnosis of LV functionality.