The nested-factors model is a well-established structural model of cognitive abilities in cognitive ability research but has not yet been used to investigate the role of cognitive abilities in job performance. Core assumptions of the nested-factors model are that a broad general mental ability (GMA) exists besides narrower abilities and that this GMA differs from the narrower cognitive abilities in breadth but not in subordination. The authors of this article propose that a recently emerging statistical technique—relative importance analysis—corresponds to the assumptions of the nested-factors model. To empirically study the implications of using the nested-factors model, the authors applied relative importance analysis to a meta-analytic matrix linking measures of 7 narrower cognitive abilities from an established ability taxonomy (Thurstone's primary mental abilities), GMA, and job performance. Results revealed that GMA accounted for 10.9% to 28.6% of the total variance explained in job performance and that GMA was not consistently the most important predictor. The discussion focuses on potential theoretical, methodological, and practical implications of the nested-factors model for personnel psychology.