In the era of digital music content-based music recommendation gained a lot of significance. It is the most widely used technique to recommend music to the users. It provides personalized music recommendations to the user based on the characteristics of the music or a song. There are numerous ways to implement the content-based music recommendation systems. This research paper aims study several approaches that are used to implement content-based music recommendation systems and one of these in greater detail. As the name suggests the content-based recommendation system focuses on the content of the music that is the characteristics or features of the music or a song and compares it with the user preferences to recommend music. In this study, we aim to investigate various methodologies employed by music recommendation systems, ranging from the analysis of intricate musical features to the application of sophisticated computer algorithmsthis research is all about figuring out how your music app knows your music taste so well. By digging into the details of these recommendation systems, we hope to understand how they work.