Abstract: With the growth in the number of video streaming services, providers have to strive hard to make relevant content available and keep customers engaged. A good experience would help customers discover new and popular videos to stream with ease. Customer streaming behavior tends to be a strong indicator of whether they found a video engaging. Aggregate customer behavior serves as a useful predictor of popularity. We discuss the use of past streaming behavior to learn patterns and predict a video’s popularity using tree ensembles.