A mutual fund is a common instrument for households and corporations to invest in the financial markets through diversified portfolios of securities. Investing in managed mutual funds involves relying on a fund manager's knowledge, expertise, and investment strategy to beat the fund's benchmark. The purpose of this paper is to help mutual fund investors in their fund selection process. The fuzzy-set qualitative comparative analysis (fsQCA) is the methodology applied to identify combinations of factors that facilitate the selection of performing mutual funds. The goal is to determine whether fund manager skill, as measured by Jensen's Alpha and other qualitative factors, is a key driver of performance. Our research focuses on US-registered equity funds with a global investing scope over a 5-year period (2016-2021), and we combine three mutual fund databases to obtain more complete data while enhancing data accuracy and consistency. The findings reveal that both manager skill and fund size are pervasive factors included in all three successful combinations of sufficiency conditions leading to high-performance funds. In addition, it is verified that manager skill is the only necessary condition to ensure high returns on mutual funds. Investors' fund selection process is a cumbersome task that can be simplified with the successful recipes provided by the fsQCA model.