The implementation of data-driven decision-making practices (DDDM) is a key component of contemporary teachers' professional practice. As such, the measurement of DDDM and related constructs is important for multiple purposes in both research and practice (e.g., identifying teacher needs around DDDM, and monitoring teacher change in response to DDDM interventions). With the present study, we examined the score factor structure and reliability of the Data-Driven Decision-Making Efficacy and Anxiety Inventory (3D-MEA), an existing measure of data-driven decision-making-related self-efficacy and anxiety. Prior work with this instrument has provided some internal structure and reliability evidence in the context of teachers from the Pacific Northwest. Confirmatory factor analysis of 3D-MEA scores from a sample of Midwestern teachers replicates the initially hypothesized five-factor internal score structure. Our study also affords evidence of high score reliability within this population. Limitations, implications, and future directions are discussed.