International Journal of Research and Development in Engineering Sciences https://www.ijrdes.com Dr. R. Triveni 6 3 (May - June) 2024 06 May-June enLearningChronic Kidney Disease(CKD)DatasetSupport Vector Machine(SVM)Decision TreeANN. The diagnosis of kidney disease often called chronic renal illness is known as chronic kidney disease CKD Chronic kidney disease CKD is a widespread and chronic health issue that requires preventative measures for early identification in order to slow the diseases progression Using complex techniques like Support Vector Machine SVM and Logistic Regression this study explores the field of machine learning For robust model construction use Random Forest and Decision Tree Through the use of Variance Inflation Factor VIF for feature engineering the dataset is carefully refined to improve the visibility of relevant features To address any possible data imbalance concerns Synthetic Minority Oversampling Technique SMOTE is also utilized promoting a fairer representation of classes in the dataset By means of a thorough assessment procedure the study methodically pinpoints the key elements that contribute to a precise diagnosis of chronic kidney disease Each algorithms effectiveness is evaluated using performance indicators like recall accuracy precision and Flscore Copyright (c) 2026 International Journal of Research and Development in Engineering Sciences. All rights reserved. 2024 All Rights Reserved