In recent times streaming platforms such as Spotify, Apple music, etc. have become the go to source of music on the go. The main challenge for a new upcoming artist is to make his music reach a wider audience. The proposed system makes use of a machine learning/ deep learning based model to predict if a music would likely break into the top 50 musics globally on streaming services like Spotify . The proposed system will analyze parameters like acousticness, danceability, , time, signature, mode, tempo, valence, time duration , keys to determine the qualities of the ideal musics which is supported by a dataset of the top musics throughout time. The system will offer suggestions for how to make a music better depending on commercial factors. The proposed framework will predict whether or not a music will hit the top 50 or not based on commercial