The main objective of this study is to predict and monitor groundwater quality through the use of modern Machine Learning (ML) techniques. By employing ML techniques, the research effectively evaluates groundwater quality to forecast its future trends. Five machine learning models Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), Adaptive Boosting (AdaBoost), Extreme Gradient and Boosting (XGBoost) were used here to predict the water quality by assessing the physical and chemical parameters such as electrical conductivity (EC), hydrogen ion (pH) concentration, total dissolved solids (TDS), chemical parameters such as, sodium (Na