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Today, all higher education institutions, especially computer and engineering colleges, face challenges in the admissions process. Each university should strive for an admissions system based on valid and reliable admissions criteria that select candidates likely to succeed in its programs. In addition, each university should use the best possible techniques for predicting applicants' future academic performance before admitting them. This would support university decision-makers as they set efficient admissions criteria. However, most higher education institutions face challenges when they analyze their large educational databases to predict students' performance. This is because they use only conventional statistical methods rather than new and efficient predictive techniques such as Educational Data Mining, which is the most popular technique to evaluate and predict student performance.