The fundamental target of advanced education foundations is to give quality instruction to its understudies. One approach to accomplish most elevated amount of value in advanced education framework is by finding learning for expectation with respect to enrolment of understudies in a specific course, distance of conventional classroom showing model, discovery of out of line implies utilized as a part of online examination, identification of irregular qualities in the outcome sheets of the understudies, forecast about understudies` execution et cetera. The information is covered up among the instructive data set and it is extractable through data mining procedures. Show paper is intended to legitimize the capacities of data mining strategies in setting of advanced education by offering a data mining model for advanced education framework in the college. In this examination, the order undertaking is utilized to assess understudy`s execution and as there are numerous methodologies that are utilized for data characterization, the choice tree strategy is utilized here. By this assignment we extricate learning that portrays understudies` execution in end semester examination. It helps prior in recognizing the dropouts and understudies who require exceptional consideration and enable the educator to give proper prompting/guiding.

Educational Data Mining (EDM); Classification; Knowledge Discovery in Database (KDD); ID3 Algorithm

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