This research-in-progress paper draws on an extensive body of literature related to student retention. The purpose of this study is to develop a student retention model utilising student demographic data and a combination of data from student information systems, course management systems and other similar tools to accurately predict academic success of students at our own institution. Our research extends Tinto’s model by incorporating a number of components from Bean’s, Astin’s and Swail’s model. Our proposed eclectic model consists of seven components, identified as determinants of student retention. The strength in the model lies in its ability to help institutions work proactively to support student retention and achievement. The proposed research methodology to be used in this study is “a mixed-methods concurrent triangulation strategy”. The results are expected to indicate which of the factors are most important in developing an information system to predict and suggest interventions to improve retention.