The Credibility Revolution advances quantitative research designs intended to identify causal effects from observed data. The ensuing emphasis on internal validity however has enabled the neglect of construct and external validity. This article develops a framework we call causal specification. The framework formally demonstrates the joint necessity of assumptions regarding internal, construct and external validity for causal generalization. Indeed, the lack of any of the three types of validity undermines the Credibility Revolution’s own goal to understand causality deductively. Without assumptions regarding construct validity, one cannot accurately label the cause or outcome. Without assumptions regarding external validity, one cannot label the conditions enabling the cause to have an effect. These assumptions ultimately are founded on qualitative and theoretical understandings of a causal process. As a result, causal specification clarifies the central role of qualitative research in underwriting deductive understandings of causality in quantitative research.