YouTube is a global platform on which its users can upload their videos and have interactive review of other users through built-in features such as like, comment, rate, share, upload content, and save. A few videos which have tremendous number of views and likes over an explicit span of time become overly favored and such videos are known as ‘Trending YouTube Videos’. This research suggests predicting whether ratings for a Trending YouTube video are disabled. The sensitivity of a video’s content can be determined by its YouTube ratings. It is implied that a video has restricted or sensitive content and is not intended for children if there is no rating, i.e., ratings disabled. Research is based on data from 999 YouTube videos that were trending within a specific time period. Statistics consists of the number of views, likes, dislikes and comment counts, the research was performed using the following models of Machine Learning namely Random Forest, Decision Tree, Support Vector Machine, Logistic Regression, and K-Nearest Neighbor.