REICE. Revista Iberoamericana sobre Calidad, Eficacia y Cambio en Educación

Predicting academic performance in Peruvian university students is a guarantee to meet licensing and accreditation requirements. A transversal, comparative and explanatory (predictive) design was used to establish the resilience and coping factors that predict academic performance, in two stratified probabilistic samples from private universities in Lima.The RESI-, CAE, Smilkstein, CP-LS and DWLS estimators, GLS, showed that the predictive model of resilience and weighted average have an effect on the perception of academic performance and a minimal effect on the weighted average. Both factors predict academic performance directly, indirectly and relationally. The self-confidence factor, social capacity, open emotional self-targeting strategies, open emotional exposure and social family support are highlighted as relevant predictors in expectation of achievement, perceived learning and overall satisfaction. Family functioning is an indirect predictor through the resilience of academic performance. Factors of active coping better predict the perception of performance than protection and risk factors. Large homogeneous samples with psychometric value can improve predictive models, identify profiles, design causal studies, develop talent learning programs and active strategies that would improve the quality of university learning.