In data science, choosing the right machine learning algorithms is essential for getting the best possible predicted performance. To investigate the effectiveness of different machine learning algorithms, a thorough analysis is conducted within the WEKA software framework. A suitable venue for this investigation is WEKA, a popular platform for machine learning and data mining activities that offers a wide range of algorithms. Our study compares and assesses the effectiveness of several machine learning algorithms on various datasets, taking into account variables like scalability, accuracy, and computing economy. Using a strict approach, analyses for patterns and trends provide insight into the advantages and disadvantages of particular algorithms in different contexts. The research attempted to utilize many machine learning algorithms to determine the accuracy of the dataset after deleting particular fields.