This chapter explores the use of machine learning in subsurface geothermal resource development. In this regard, it reviews machine learning applications in various research areas, including exploration, drilling, seismicity, reservoir management, production, and geothermal operational optimization. A review of the relevant literature indicates the recent significant progress of machine learning in the geothermal industry. Despite the numerous advancements in deep learning for geothermal modeling, several challenges persist. These challenges include data accessibility, data refinement specifically for machine learning purposes, and the need for specialized education on artificial intelligence in the energy sector, particularly in the field of geothermal energy.