This work presents a machine learning-based diagnostic system for automated kidney and liver disease analysis. Our approach leverages advanced ML algorithms to analyze clinical data, medical imaging, and laboratory results to provide early detection and accurate classification of kidney and liver pathologies. The system achieves high accuracy in identifying conditions such as chronic kidney disease, liver cirrhosis, and fatty liver disease, enabling healthcare providers to make faster, data-driven diagnostic decisions. By integrating predictive analytics with clinical workflows, our solution addresses the growing need for scalable, cost-effective diagnostic tools in healthcare settings. The system demonstrates significant potential for improving patient outcomes through early intervention and personalized treatment planning.