Intrapreneurs, entrepreneurial employees, constitute an important force behind innovations in the economy. Yet, what factors that promote intrapreneurship at the country level are an underdeveloped research area. This paper provides an important contribution regarding the methodological approach and the broad set of potential explanatory factors studied. Based on machine-learning techniques (Least Absolute Shrinkage and Selection Operator (LASSO) and Extreme Bounds Analysis (EBA)), we investigate the influence of over 60 factors capturing institutional, demographic, cultural, and developmental factors. We find that the quality of government measured as impartiality, i.e. that the public institutions treat the citizens in a non-discriminatory fashion and do not favor some groups or individuals, and the level of human capital, measured as the average years of schooling, are the most important factors predicting the level of intrapreneurship across countries. Instrumental variable results support a causal interpretation. The findings emphasize the importance of policy to establish well-functioning and impartial institutions as well as to promote higher education.