This study addresses a shortcoming in the transformational leadership literature (Van Knippenberg & Sitkin The Academy of Management Annals, 7(1), 1-60, 2013) by demonstrating when and how individual transformational leadership components may predict high and low team performance, as well as how these behaviors can combine to achieve certain outcomes. The study also sheds light on how certain team leader’s demographics (i.e., leader sex, age, and tenure) and team context conditions (i.e., team size and job complexity) predict different team performance outcomes via different transformational leadership behaviors. A case-based asymmetric configurational approach and fuzzy-set qualitative comparative analysis (fsQCA) were used to examine data gathered from 59 teams in the marketing and print services sector. The results identified multiple useful configurations of transformational leadership behaviors and team leader demographics/team context conditions that accurately predict high and, separately, low team performance (i.e., achieving model prediction accuracy odds of 4 to 1 or greater). A predictive validation was also performed on a second sample whereby the highly consistent models for the study’s main sample had high predictive abilities for this second sample. From a practical standpoint, this study suggests that certain configurations of transformational sub-components may work better for some leaders than others (e.g., young female versus male leaders). It also identifies more realistic, authentic, and potentially less costly strategies for predicting high (and avoiding low) levels of team performance in different contexts. Finally, this study contributes to the literature by being a first attempt to apply an asymmetric approach to transformational leadership research.