The aim of research paper is to improve the current trends in the higher education systems to understand from the outside which factors might create loyal students. The necessity of having loyal students motivates higher education systems to know them well, one way to do this is by using valid management and processing of the students database. Data mining methods represent a valid approach for the extraction of precious information from existing students to manage relations with future students. This may indicate at an early stage which type of students will potentially be enrolled and what areas to concentrate upon in higher education systems for support. For this purpose the data mining framework is used for mining related to academic data from enrolled students. The rule generation process is based on the decision tree as a classification method. The generated rules are studied and evaluated using different evaluation methods and the main attributes that may affect the student’s loyalty have been highlighted. Software that facilitates the use of the generated rules is built using VB.net programming language which allows the higher education systems to predict thestudent’s loyalty (numbers of enrolled students) so that they can manage and prepare necessary resources for the new enrolled students.