: In order to accurately predict the water-richness of the weathered bedrock aquifer, a weathered bedrock aquifer water-richness discrimination model based on Whale Algorithm Optimized Support Vector Machine (WOA-SVM) is proposed by using 28 sets of weathered bedrock pumping test boreholes in Zhangjiamao minefield as the training and validation samples, and selecting the lithological assemblage index, weathering index, thickness, core take rate, and depth of burial of the weathered bedrock as the evaluation indexes. The model can predict the water-richness level of the weathered bedrock in the area without pumping test data, and comprehensively utilize the geological information of 249 groups of exploration boreholes in the wellfield to realize the water-richness zoning of the weathered bedrock in the minefield. The study shows that the weathered bedrock of Zhangjiamao minefield is weakly water-rich as a whole, and its spatial distribution is uneven; there are strong water-rich areas in the central part of the field and the local area along Wulanbula Gully, but their distribution range is small, there are some moderately water-rich areas in the central-western and southeastern parts, and the northeastern and southwestern areas are weakly and very weakly water-rich almost all the time. The results predicted by this method are more in line with the actual situation, and the research results can provide a reference for the safe production of the mine and a new way of thinking for the prediction of the water-richness of the weathered bedrock.