This article is a review on attributes, models and tools used to solve the problem of predicting students' academic performance. Based on the reference throughout 2009, the attributes used include demographic, academic grades, school related and social attributes. The academic score attributes are the results of the percipient along their studies, while the school-related attributes are result for few subject taken in high school. Demographic and social attributes are family background and the daily interactions of respondents. These tools are supporting a lot of rule mining algorithms like clustering, classification and association, to use on datasets of different types.