Causal prescriptive statements are valued in the social sciences when there is the goal of helping people through interventions. The articles in this special issue cover different methods for testing causal prescriptive statements. This commentary identifies both virtues and liabilities of these different approaches. We argue that it is extremely difficult to confirm causal prescriptive statements because of the potentially infinite number of third variables in causal relationships and of confounding variables in experimental manipulations. All methodological approaches, including randomized control trials, have a simple view of causality that does not adequately solve the challenges of indeterminacy, interactions, combinatorial explosion, and dynamics. However, these challenges should not discourage researchers from formulating and testing causal prescriptive statements.