This article discusses the main background and aspects of a research project that will utilize Educational Data Mining to analyse academic performance. The project is a continuation of several studies conducted at the National University of the Northeast (Argentina), the Resistencia Regional National Technological University (Argentina), and the National University of the East (Paraguay). In all these projects, Educational Data Mining was used to generate descriptive and predictive models of academic performance based on the academic, socio-economic, and attitudinal profiles of students in various subjects. The research will focus on identifying the variables that significantly impact the academic performance of students in the subjects “Algorithms and Data Structures” and “Systems and Organisations,” aiming to guide actions to help prevent dropout by addressing the identified causes. This topic is highly relevant, timely, and applicable to UNCAus (National University of Chaco Austral, Argentina). The project will provide concrete conclusions and experiences regarding all the aspects that need to be considered when detecting the variables influencing students’ academic performance.