The goal of making an appropriate product recommendation is to predict customer behavior patterns while taking into account the situation of the online retail and streaming industries. When it comes to songs, the language in which they are sung, the vocalists, and, most crucially, the genre of music can all play a big role. The listener’s behavioral patterns and demographic background are very important. Using a few recommenders’ system-based approaches, the study model described in this chapter predicts customers’ behavior patterns based on demographic data and historical behavior patterns. The model was developed after researching numerous machine learning methods based on recommender systems. With an accuracy of 92.1% and a precision of 90.1% on our dataset, model-based collaborative filtering outperformed the other strategies used. With the suggested model’s ability to perform better than the existing works discussed in the related work section, the main goal has been accomplished.