CKD doesn't have any distinct symptoms, it can be difficult to anticipate and prevent, which may result in long-term health issues. Here, it was intended to reduce diagnostic lead time and boost precision. The major goal of this work is to develop a predictive model for chronic kidney disease using data analysis and several machine learning techniques. Accuracy will be determined by contrasting various algorithms, including SVM, Random forest, and Naive Bayes.