We applied machine learning to investigate how the solar wind and Earth's geomagnetic activity control the position of the magnetopause, the boundary layer of Earth's magnetic field. Our results demonstrate that geomagnetic activity strongly influences this boundary and should be incorporated in predictive models. Using data from multiple spacecraft, we developed a simple mathematical description of the magnetopause distance that improves understanding of solar wind–magnetosphere interactions.