This paper considers recent efforts to conduct experimental and quasi-experimental evaluations of career and technical education programs. It focuses on understanding the counterfactual, or control population, for these program evaluations, discussing how the educational experiences of the control population might vary from those of the treated population and the ways in which the treatment and control populations used for evaluation may differ from each other. The paper begins by discussing the key identification strategies and the associated assumptions used to identify program effects, including regression and propensity score matching, instrumental variables, regression discontinuity designs, randomized controlled trials, and lottery-based admissions. It then presents a series of case studies evaluating the counterfactual for specific studies that used each identification strategy.