Business process models are essential for the development of information systems, facilitating communication and understanding by visually representing activities and flows. The comprehensibility of these models is crucial and depends on various personal and model-related factors. This article presents an empirical study conducted with 52 undergraduate students aiming to identify the most relevant personal and model-related factors, using BPMN syntax and covering aspects of process logic and modeling notation. The applied methodology included Principal Component Regression (PCR) to determine the key factors affecting comprehensibility in terms of effectiveness and efficiency. As a result, the structural complexity of the model, element labeling, and personal factors such as modeling experience and knowledge of business processes are crucial for effectiveness. Regarding efficiency, comprehensibility is affected by structural complexity, element labeling, age, gender, and model density. Reducing independent variables from 37 to 11 in terms of effectiveness and 9 in terms of efficiency provides a clearer insight into the influencing factors.