We report results from the following three analyses of PARCC [Partnership for Assessment of Readiness for College and Careers] cognitive complexity measures, based on 2014 field test item and task development and field test data. We conducted classification and regression tree analyses using 2014 PARCC field test data to do the following: (1) Predict item difficulty and discrimination for samples of PARCC ELA and mathematics items and tasks and evaluate the interpretability and usability of the results for assembling operational test forms; (2) Evaluate the explanatory power of the four ELA and five mathematics cognitive complexity sources and propose final explanatory models; and (3) Demonstrate how regression tree results can be used to assemble operational test forms In addition, we surveyed cognitive complexity coders at Pearson to capture their insights and recommendations for PARCC on the cognitive complexity framework, training of complexity coders, the coding process and decision making, and future considerations for cognitive complexity. We also conducted a focus groups with ELA/literacy and mathematics coders to examine more closely responses to selected survey questions.