The sustainable management of water relies heavily on groundwater resources, and an important aspect of their effective utilization is artificial recharge. In the specific case of the Murredu watershed in India, a comprehensive approach is proposed in this research, integrating Geographic Information Systems (GIS), Remote Sensing (RS), and Multi-Criteria Decision Making (MCDM) techniques. The aim is to delineate groundwater potential zones (GWPZs) and identify suitable locations for artificial recharge. Several thematic layers, such as slope, drainage density, geomorphology, land use land cover (LULC), curvature, soil, topographic wetness index (TWI), rainfall, distance from the river, and elevation, were considered in this study. To ascertain the relative importance of these thematic maps in influencing groundwater availability and recharge, the Analytic Hierarchy Process (AHP) and Fuzzy-AHP techniques were employed to assign weights. Utilizing a weighted overlay technique within a GIS environment, the GWPZs map was generated. Within the study area, the GWPZs were categorised as poor, moderate, and high based on the AHP and Fuzzy-AHP models. According to the AHP model, 14.93% of the GWPZs in the region were classified as poor, 73.53% as moderate, and 11.54% as high. On the other hand, the Fuzzy-AHP model classified 14.02% as poor, 76.55% as moderate, and 9.44% as high. The accuracy of these classifications was verified using the receiver operating characteristic curve (ROC) and area under the curve (AUC), resulting in accuracy rates of 71.4% for AHP and 77.6% for Fuzzy-AHP. Additionally, the study employed RS and GIS techniques to develop a map by overlaying the drainage density and lineament density maps. This approach helped identify 126 potential sites for artificial recharge based on the best-performing Fuzzy-AHP model. The insights gained from this study facilitate the sustainable management and planning of groundwater resources, ensuring their availability and sustainability for future generations.