The disobedience of priority rules makes unsignalized intersections riskier under mixed traffic scenarios. Small-size vehicles move parallel to large-size vehicles, accept a gap in their shadow and haphazardly move into the intersection. So, the critical gap estimation in this situation is a complex task. In that context, the present study is focused on estimating the critical gap of vehicles and developing a logistic regression model to analyze the drivers’ aggressiveness at unsignalized intersections. The critical gap was estimated for right turning and through movements using the clearing behaviour approach. To understand the risk-taking behavior of two-wheelers, their critical gap was compared with the cars and observed that 77% of vehicles were behaving aggressively. So, the parameters that influence the aggressive behavior of drivers were identified and included while developing the model. The proposed model can predict the drivers’ aggressiveness with 92.85% accuracy in mixed-traffic scenarios.