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The high dropout rates in undergraduate courses have become increasingly worrying in Brazil, this problem has generated losses both for the country, as for students and universities. In this context, the aim was to identify students with a tendency to dropout through a case study, conducted at the Federal University of Ceará, through data mining techniques and using historical data of students, in which experiments were conducted with two different scenarios, the first scenario having the total number of records with the division of records by unbalanced classes and the second scenario containing a sample of records with the division between balanced classes.