This study aims to identify the critical factor(s) that determine the embeddedness level (EL) of rural entrepreneurs. In order to achieve this aim, existing applied studies on the embeddedness of entrepreneurs undertaken in different rural areas were systematically collected to create a database in order to provide the material for a systematic comparative analysis. This was done in order to highlight common and contrasting findings from a set of selected studies for different ELs. As many results of these studies were largely qualitative in nature and only partially comparable, a specific tool for analysing categorical data based on artificial intelligence methods, namely, rough set data analysis (RSDA), was employed. This experimental study is the first RSDA approach that compares the results of several rural case studies and infers general induction rules for the different ELs. The results of our analysis show that using and benefiting from local resources are the key factors that explain how entrepreneurs become embedded in rural areas.