This research presents a comprehensive framework for the development of the Kidney Care Mobile Application-KidniFy, leveraging advanced machine learning and Internet of Things (IoT) technologies. By amalgamating predictive models for kidney disease risk assessment, radiology image interpretation, water quality assessment, and personalized dietary guidance, the application aims to transform kidney care in Sri Lanka. Notably, the predictive model achieves impressive accuracy, precision, recall, and F1-score values for kidney disease risk prediction. The convolutional neural network (CNN) for radiology image analysis demonstrates exceptional classification accuracy, while the IoT-based water quality assessment system provides real-time insights into water contamination risks. Additionally, the personalized diet recommendation system generates tailored dietary plans for kidney disease patients based on comprehensive data. Ethical considerations underscore data privacy and security. With its potential to revolutionize kidney care, this research underscores the power of technology to enhance patient outcomes and addresses the challenges of chronic kidney disease.