Groundwater serves as a critical resource for drinking, irrigation and industrial purposes within the Sarada River basin, Andhra Pradesh, India. Sarada basin is currently witnessing pressures stemming from unsustainable practices, climate fluctuations and population growth. An essential step toward achieving sustainable groundwater management within this specific context is the delineation of groundwater potential zones. These zones can be effectively mapped through the integration of Remote sensing (RS) and Geographic Information System (GIS) technologies and by amalgamating diverse thematic layers encompassing geology, geomorphology, drainage, slope and land use tailored to the unique conditions of the Sarada Basin. Additionally, a machine learning approach was employed by integrating algorithms such as support vector machines (SVM) and AHP multi-criteria into the methodology to enhance the accuracy of groundwater potential zone delineation by learning various diverse datasets and the spatial relationships between various environmental factors within the Sarada River basin.