Our research addresses the pressing global issue of liver diseases by developing a robust Liver Disease Prediction (LDP) system using comprehensive patient datasets. We evaluate and compare multiple machine learning algorithms such as K-Means, Logistic Regression, Decision Trees, and Support Vector Machines to accurately classify chronic liver conditions. Through extensive data analysis and confusion matrix evaluations, we demonstrate significant improvements in prediction accuracy, providing reliable tools for early diagnosis and intervention. This innovative application of machine learning not only aids healthcare professionals in managing liver disorders effectively but also reduces diagnostic workload, thereby enhancing overall patient care and medical outcomes.