The aim of this research was to develop machine learning logistic regression model to classify students from BIH and EU based on their entrepreneurial intentions, entrepreneurial mindset dimensions, resources and demographic and academic characteristics. Logistic regression coefficients were used to analyze the impact of variables on model output. The results showed that the increase in variable values of Entrepreneurial intention, Confidence, Action-oriented, as well as being in the Master study cycle increase the odds ratio that the student is from BIH, while increase in variable values of Peculiarity, Innopreneurship, Innovation-oriented, Experience, Risk acceptance, Need to achieve, Persistence, Resources, Age, as well as being male and being in the Bachelor study cycle decrease the odds ratio that the student is from BIH, increasing the probability that the student is from the EU. This research contributes to better understanding how entrepreneurial intentions, entrepreneurial mindset dimensions, and demographic and academic characteristics vary between students with different economic, social and educational backgrounds.