Chronic kidney illnesses are currently affecting a large number of individuals globally. Because of the numerous risk factors, including the diet, environment, and quality of living .Many individuals get abrupt illness without knowing why. Many people throughout the world are today affected by Chronic Kidney diseases. The diagnosis of chronic renal disease is usually invasive, costly, time-consuming, and risky. Early sickness detection techniques are still essential, especially in developing countries where infections are sometimes only found after they are too progressed. The need to address the problems and circumvent obstacles made this inquiry necessary in the state of them. The diagnosis when dealing with CKD is often invasive, expensive, time-consuming, and frequently dangerous. That is the reason why many people leave it untreated till late stages, especially in those nations with little resources. Consequently, the early detection method for the disease is predicted in the proposed method of this paper. In order to predict we have taken the help of machine learning. We have used the Artificial Neural Networks to predict the patient kidney disease present or not.