Massive Open Online Courses (MOOCs) typically present a high rate of non-completing learners. Studying the characteristics of pass and fail learners should help to provide assistance and identify root causes for dropouts. In this work, we propose to improve a success prediction task on a specific course with a solution based on a transfer learning approach. Our experiments are validated on two datasets with different trace properties.