Background:

school dropout should be analyzed in a multivariate context to identify its causes and effects; in no way, it should be attributed to a single cause.

Objective:

to determine the predictive capacity of some factors on the school dropout of medical students, through a multiple logistic regression model.

Methods:

an analytical, predictive study was carried out in 87 medical students enrolled in the 2015-2016 academic year. Theoretical and empirical methods were applied and it was carried out in two stages: in the first, the variables most associated with school dropout were identified through a bivariate analysis; and in the second, the ability of these variables to predict dropout was analyzed through logistic regression (multivariate analysis).

Results:

in the bivariate analysis, nine variables showed a significant relationship with school dropout; when subjected to multivariate analysis (correlation and logistic regression), only four maintained statistical significance, that´s why they were finally chosen as predictor variables.

Conclusions:

school dropout in Medicine students can be predicted by the synergistic combination of the four predictors: dedicating less than 15 hours per week to study, female sex, school repetition and low academic performance in Morphology-physiology.

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