Driving behavior is a complex human behavior shaped by the interplay of cognitive processes, emotional factors, and demographic characteristics. Despite substantial advances in driving psychology, evidence on the combined contribution of psychological and demographic factors to different dimensions of driving behavior remains limited. This study examined the predictive effects of aggression, anxiety, age, and gender on four dimensions of driving behavior—slips, errors, deliberate violations, and unintentional violations—using the Manchester Driver Behaviour Questionnaire (DBQ) framework. A cross-sectional study was conducted with 92 drivers who had at least three years of driving experience. Data were collected using the standard DBQ and a researcher-developed questionnaire assessing aggression and anxiety. Pearson correlation and multiple linear regression analyses were performed to analyze the data. The results showed that aggression was positively and significantly associated with all four dimensions of driving behavior and was the strongest predictor across all regression models. In contrast, anxiety was not significantly associated with any dimension of driving behavior. Among the demographic variables, age showed a significant negative association with some dimensions of driving behavior, whereas gender was not a significant predictor. The regression models explained between 27% and 32% of the variance in driving behavior. These findings suggest that interventions targeting aggression management may be more effective in improving driving behavior than those focusing solely on demographic characteristics.