Few studies have been conducted to perform an in-depth examination of cyberbullying roles and to identify multifaceted factors associated with cyberbullying roles. Using Latent Class Analysis, the current study identified four cyberbullying roles (i.e., cyberbully, cyber victim, cyberbully victim, and noninvolved) based on the data from the 2009-2010 Health Behavior in School-Aged Children study in the United States. Multinomial logistic regressions were constructed to determine the social-ecological factors related to different cyberbullying roles. Certain individual, family, peer, and school factors were found to be associated with distinctive cyberbullying roles. There were common and unique predictors observed that distinguished cyberbullies, cyber victims, and cyberbully victims. Findings suggest the importance of considering both common and unique factors in intervention strategies targeting specific cyberbullying roles. Improving the effectiveness of cyberbullying intervention and prevention programs also requires attention to multifaceted domains and tailoring programs to the population served.