The study focuses on understanding the air and oil flow characteristics within a ball bearing during high-speed rotation, with a particular emphasis on optimizing frictional heat dissipation and oil lubrication methods. Computational fluid dynamics (CFD) techniques are employed to analyze the intricate three-dimensional airflow and oil flow patterns induced by the motion of rotating and orbiting balls within the bearing. A significant challenge in conducting three-dimensional CFD studies lies in effectively resolving the extremely thin gaps existing between the balls, races, and cages within the bearing assembly. In this research, we adopt the ball-bearing structured meshing strategy offered by Simerics-MP+ to meticulously address these micron-level clearances, while also accommodating the rolling and rotation of individual balls. Furthermore, we investigate the impact of different designs of the lubrication ports to channel oil to other locations compared to the ball bearings. This analysis is pivotal, as it allows us to assess the effects of these bearing weirs on spin loss, which, in turn, has a substantial influence on the overall efficiency of an electric motor. This holistic understanding of spin loss is crucial in the context of battery electric vehicles (BEVs), as it directly affects the vehicle’s range and energy efficiency. In conclusion, this research not only sheds light on the intricate airflow dynamics within ball bearings but also underscores the practical significance of mitigating spin loss in electric motors, thus contributing to the advancement of BEV technology and its environmental sustainability.