The rapidly changing nature of work has increased the importance of non-routine thinking skills required to make decisions under risk and uncertainty. Cognitive ability tests are traditionally considered a robust tool for personnel selection and placement, provided how they assess thinking skills that generalize across many jobs. Tests are often designed to measure general cognitive ability, which is conceptualized as the foundation of higher-order thinking skills. However, other studies have suggested that tests of specific abilities are useful as well. There is growing evidence that numeracy, defined as the ability to apply mathematics in practice, is a strong predictor of decision-making skills. However, much remains to be examined in terms of numeracy’s usefulness as a predictor relative to commonly used cognitive ability tests. In this dissertation, I review decision-making competence as a multidimensional performance criterion, in which each of its dimensions have implications for workplace decisions. Using a sample of 355 undergraduate students who completed a battery of assessments, I estimated the relative importance of crystallized ability, fluid ability, and statistical numeracy for predicting overall decision-making competence and the dimensions that comprise it. This study builds on previous incremental validation studies by adopting dominance analysis to partition criterion variance. Numeracy was consistently a superior predictor over fluid ability, whereas the relative importance of numeracy and crystallized ability varied across dimensions. These results contribute to a growing literature on statistical numeracy as an important part of decision-making that is underrepresented in traditional cognitive ability tests. Implications are discussed with respect to the importance of leveraging numeracy in personnel selection and training systems for jobs that require decision-making competence.