Genetic polymorphism of the SLC6A4 gene is associated with several behavioral disorders, including depression. Since studying the total nonsynonymous single nucleotide polymorphisms (nsSNPs) of the SLC6A4 gene at the population level is a difficult task, we aim to utilize in silico approach to detect the most deleterious nsSNPs of the SLC6A4 gene. In our study, 7 computational tools were used in the initial stage, including SIFT, Polyphen-2, PROVEAN, SNAP2, PhD-SNP, PANTHER, and SNPs&GO to find out the most damaging nsSNPs.