Random Forest algorithm provided the best prediction accuracy compared to other algorithms like Decision Tree Classifier, K-Neighbors Classifier, SVM, Naive Bayes, Bagging Classifier, AdaBoost Classifier, and MLP Classifier. All the algorithms generated models from the training dataset and new data was applied to the trained models to predict the class. Random Forest algorithm achieved a prediction accuracy of 98.62% on the test data, which was higher than other algorithms.