Sourcing top entrepreneurial executives has proven challenging to many organizations as the recruitment processes are complex and onerous. Our goal for this study is to optimize one such process used at Purdue University’s venture studio where entrepreneurs are assessed in three phases, their experience and skills (demographic), a behavioral leadership assessment, and through qualitative observed interactions and expressions coming out of motivational-based interviews. A mixed methods approach was employed to examine past entrepreneurial candidates (N=116) to identify the key factors of top performance. Our research discovered that only one of a dozen demographic factors, startup experience, was significant in candidate performance. Of higher impact were select leadership assessment measures, namely attitudes toward proactivity, independence, people orientation, and genuineness. In addition, three key qualitative observed behaviors, passion, empathy, and curiosity, were found to determine candidate success, accounting for nearly 50% of the performance outcome. Unfortunately, there were no precursors identified as dominant predictors that could help to eliminate or simplify successive recruiting phases. Our research integration phase utilized cluster analysis and ANOVA techniques in an attempt to define success personas for both the quantitative and qualitative measures. Although we could not distinctly identify the attributes of the top-tier candidates, we were able to identify provisional personas for poor candidate clusters in both quantitative affective measures and qualitative observed behaviors. It is anticipated that the use of these low-tier personas will lead to quicker disqualification, saving time and effort with fewer candidates being processed overall.