Background: Fundamental problems with Personality Disorders (PD) diagnostic system in the previous version of DSM, led to the revision of DSM. Therefore, a multidimensional system has been proposed for diagnosis of personality disorder features in DSM-5. In the dimensional approach of DSM-5, personality disorders diagnosis is based on levels of personality functioning (Criteria A) and personality trait domains (Criteria B). Objectives: The purpose of this study was firstly, to examine the DSM-5 levels of personality functioning in antisocial and borderline personality disorders, and second, to explore which levels of personality functioning in patients with antisocial and borderline personality disorders can better predicted severity than others. Patients and Methods: This study had a cross sectional design. The participants consisted of 252 individuals with antisocial (n = 122) and borderline personality disorders (n = 130). They were recruited from Tehran prisoners, and clinical psychology and psychiatry centers of Razi and Taleghani Hospitals, Tehran, Iran. The sample was selected based on judgmental sampling. The SCID-II-PQ, SCID-II and DSM-5 levels of personality functioning were used to diagnose and assess personality disorders. The data were analyzed by correlation and multiple regression analysis. All statistical analyses were performed using the SPSS 16 software. Results: Firstly, it was found that DSM-5 levels of personality functioning have a strong correlation with antisocial and borderline personality symptoms, specially intimacy and self-directedness (P < 0.001). Secondly, the findings showed that identity, intimacy and selfdirectedness significantly predicted antisocial personality disorder severity (P < 0.0001). The results showed that intimacy and empathy were good predictors of borderline personality disorder severity, as well (P < 0.0001). Conclusions: Overall, our findings showed that levels of personality functioning are a significant predictor of personality disorders severity. The results partially confirm existing studies.