As on-demand streaming technology rapidly expanded, binge-watching (i.e., watching multiple episodes of TV series back-to-back) has become a widespread activity, and substantial research has been conducted to explore its potential harmfulness. There is, however, a need for differentiating non-harmful and problematic binge-watching. This is the first study using a machine learning analytical strategy to further investigate the distinct psychological predictors of these two binge-watching patterns. A total of 4275 TV series viewers completed an online survey assessing sociodemographic variables, binge-watching engagement, and relevant predictor variables (i.e., viewing motivations, impulsivity facets, and affect). In one set of analyses, we modeled intensity of non-harmful involvement in binge-watching as the dependent variable, while in a following set of analyses, we modeled intensity of problematic involvement in binge-watching as the dependent variable. Emotional enhancement motivation, followed by enrichment and social motivations, were the most important variables in modeling non-harmful involvement. Coping/escapism motivation, followed by urgency and lack of perseverance (two impulsivity traits), were found as the most important predictors of problematic involvement. These findings indicate that non-harmful involvement is characterized by positive reinforcement triggered by TV series watching, while problematic involvement is linked to negative reinforcement motives and impulsivity traits.