Chronic Kidney Disease(CKD) has turn into a serious issue with high growth rate, which requires kidney transplant
and Dialysis. So early detection is required to overcome CKD. In this Project, we proposed two ML algorithms to predict CKD,
one of the algorithm i.e, Naive Bayes yields a results with an accuracy of 91.54 percentage. comparing with same, KNN yields a
better result with an accuracy of 97.18 percentage. GFR (glomerular filtration rate) is used to detect CKD in its early stage
by measuring kidney functional level. Diet is recommended based on the stage. we developed a web UI for doctor who can
measure kidney function level, stages using GFR equation, upload patient treatment and suggest a diet plan for the patient.
