Numerous scholars have considered the relationship between gubernatorial power and political outcomes. In fact, gubernatorial power has been used as a key explanatory factor in analyses of topics such as gubernatorial approval, divided government, regulation, and even individual political behavior. The key to these studies is the precision with which scholars can measure gubernatorial power and many such studies rely on the Formal Powers Index (FPI)—a measure maintained by Beyle. In this article, we reconsider these commonly used power scores in three parts. First, we argue and show that FPI suffers from a key measurement error that is particularly problematic in analyses of time-series data. Second, we present a new approach to estimating gubernatorial power and explain how this approach deals with the measurement errors in the FPI. Finally, we use our new scores to replicate a study that originally relied on the FPI to analyze the effect of gubernatorial power. Given the prevalence of the FPI in the existing literature, our results have key implications for the study of the effects of gubernatorial power.