Course adviser in tertiary institution guides students on course enrolment which is part of the registration process for students. It is a phase where a student formally enrolls for requisite courses in a particular semester. Students on gaining admission are required to enroll into courses offered in their chosen programme of study every semester progressively with certain credit limits in each semester. The courses are arranged in an ascending order of complexity such that the criterion for registering for a higher course is to have passed the lower prerequisite course(s). Academic advisers are appointed for students to guide them on course enrolment but due to human factor, a lot of students end up registering for inappropriate courses which leads to inefficiency in career. This research work developed a model that classifies students as either “registrable” Or “not registerable”. Multi-layered Feedforward Neural Networks was used to develop the model that will classify students. The dataset used consists of 150 records, 4 input layers, one hidden layer, and 1output layer. The train/test split of the dataset was in the ration of 80:20. The Networks was trained for 2000 epochs. The accuracy of the model was 0.97. If a student fails more than 15 credit hours of registered courses, such student will be considered “not registerable” and hence redirected to the expert adviser for proper guidance on the course(s) to register.