**Abstract**

The aim of this study was to analyze the effects of Catechol-O-methyltransferase (COMT), Dopamine Receptor D2 (DRD2), Period Circadian Regulator 3 (PER3), Endothelial Nitric Oxide Synthetase (eNOS), Nuclear Receptor Subfamily 3 Group C Member 1 (NR3C1) functional gene variants on possible inclinations of the individuals with Substance Use Disorder (SUD) by using decision trees algorithm and to evaluate the similarities with former studies. The decision trees classification was structured by confirming the effects of genetic and epigenetic sequences of gene variants through 10 fold cross-validation under subtitles of the criminal history, continuum of substance use, former polysubstance abuse, attempted suicide, and inpatient treatment. Performance criteria were evaluated with the similarities of former studies' accuracy, sensitivity, and precision values. The branching structure of gene variants obtained by tree classification is consistent with the studies in the literature. Our study serves to be the first to show that there is a need for further comprehensive studies with data from different ethnic groups to increase the predictive accuracy rates and to state that machine learning may guide in predicting the effect of gene variants on behavior in the future.

**Keywords:** substance use disorder, COMT, DRD2, PER3, eNOS, NR3C1 gene variants, decision tree analysis, 10-fold cross validation
