This Article calls into question the fundamental premises of models of judicial decisionmaking utilized by legal and political science scholars. In the place of the predominant theories, I offer a new approach to understanding judicial behavior which recognizes judicial heterogeneity, multidimensional behavior, and interconnectedness among judges at different levels within the judiciary. The study utilizes a unique dataset of over 30,000 judicial votes from eleven courts of appeals in 2008, yielding statistically independent measures for judicial activism, ideology, independence, and partisanship. Based upon those four metrics, statistical cluster analysis is used to identify nine statistically distinct judging styles: Trailblazing, Consensus Building, Stalwart, Regulating, Steadfast, Collegial, Incrementalist, Minimalist, and Error Correcting. These judicial style types offer a fuller account of judicial behavior than any of the prior models utilized by scholars.