Contextual information of the listener is only slowly being integrated into music retrieval and recommendation systems. Given the enormous rise in mobile music consumption and the many sensors integrated into today’s smart-phones, at the same time, an unprecedented source for user context data of different kinds is becoming available. Equipped with a smart-phone application, which had been developed to monitor contextual aspects of users when listening to music, we collected contextual data of listening events for 48 users. About 100 different user features, in addition to music meta-data have been recorded. In this paper, we analyze the relationship between aspects of the user context and music listening preference. The goals are to assess (i) whether user context factors allow predicting the song, artist, mood, or genre of a listened track, and (ii) which contextual aspects are most promising for an accurate prediction. To this end, we investigate various classifiers to learn re...