Accreditation agencies request evidence of the graduates learning outcomes during quality processes. Universities have to provide exhaustive empirical proof of their achievement and development through the academic training program, which is a significant challenge because it implies a substantial improvement and change of the educational model and evaluation method. There are still theoretical gaps to explain from an empirical perspective which elements of the university curriculum are associated with academic programs learning outcomes. The lack of empirical evidence prevents us from identifying which factors are associated with an efficient achievement of learning results in higher education institutions to implement improvement actions based on valid and objective data. In this context, learning analytics is a valuable tool that can support collecting, measuring, analyzing, and reporting data to understand the different factors involved in the educational process and their influence on learning. The primary purpose of this study is to answer how to define and validate a multivariate metamodel based on the factors involved in learning outcomes and academic performance results. In this article, we present the objectives and their phases, activities, procedures, and instruments to achieve the goal of the study. We expect to validate a metamodel on a large-scale population with different academic engineering programs at the Costa Rica Institute of Technology.