Abstract
Kidney function is impacted by Chronic Kidney Disease (CKD), a chronic illness that frequently shows no symptoms. It is brought on by the body's waste materials and fluids gradually building up, and it can be inherited or the outcome of conditions like diabetes or high blood pressure. If serious consequences are to be avoided, early detection and treatment are essential. In this study, a Python-based machine learning model was developed to predict the risk of chronic kidney disease. The model takes into account a number of input features, such as baseline health measurements, medication usage, medical history, and demographic data. Estimating the risk of chronic renal disease is its main objective. Those with CKD stages 3 to 5 who are considered high-risk are given an output of “1,” whereas those who are in the early stages or do not exhibit any symptoms are given an output of “0.” The CKD risk assessment process is made simpler by this project, which provides patients and healthcare providers with a useful tool for proactive management and well-informed decision-making.