This study examines the personalization of academic trajectories in undergraduate programs classifying students based on academic, socioeconomic, and emotional dimensions. Its objective is to design a conceptual model that enables an understanding of the relationship between these factors and the curricular planning, facilitating informed academic decision-making for students and institutions. The methodology combines a theoretical and empirical approach. First, an ontology is developed to model student profiles and possible academic trajectories through a combinatorial analysis of semester workload. Then, surveys are conducted with academic administrators from various institutions to empirically describe and analyze institutional dynamics in curricular administration. The results show that the diversity of student profiles impacts academic progression, and personalized guidance is key to retention. Respondents emphasized the need for technological tools to enhance data-driven academic planning. The conclusions highlight the importance of adaptive academic recommendation models to customize trajectories and improve student progression. This study provides a conceptual and empirical foundation to strengthen academic performance management, promoting strategies supporting student retention and higher education success.