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Abstract: Machine Learning particularly Logistic Regression is used here in this study for classifying sonar signals to distinguish between “Rock” and “Mines” in underwater detection systems. Logistic Regression is a supervised Machine Learning algorithm for binary classification is chosen for its efficiency and interpretability. The process start with a sonar system that uses sound waves to detect underwater object. Features such as amplitude and frequency are extracted from the signals and used as input variable for the model. The model’s accuracy and effectiveness are validated using evaluation metrics like accuracy, precision, recall, and AUC-ROC. This classification approach enhances the safety and efficiency of underwater navigation and exploration.