This study explores the use of machine learning methods to improve morphological analysis of the Arabic language. In order to create a database of Arabic stems that academics can utilize, it examines the most well-known techniques and introduces a novel tool for finding Arabic stems from a corpus made up entirely of Arabic words.We used a corpus of 30 million Arabic words to create this database. From this corpus of words, we were able to attain a precision of 94% using our stem detection method. The benchmarking strategy and these in-depth experimental findings offer a strong basis for assessing how well our novel strategy performs.