ABSTRACT Causal inferences are a vital and intrinsic part of assessing the risk of adverse effects on human populations and ecological resources from biological, chemical, physical, and psychosocial stressors. While it is well known that a statistical association does not necessarily imply a causal association, the central role of causal theory in health and ecological risk assessment is often overlooked. In this article, we present a succinct account of causal theory in the health sciences, emphasize the importance of differentiating between formal and informal approaches to causal inference, describe the weight-of-evidence process that is currently the predominant means of inferring causality in the context of science-based regulatory decisions, and discuss the effects of causal theory on the current and future practice of risk assessment. Our aim is to highlight the significance of decisions about causation and causal inference, and to suggest that explicit, well-considered choices will serve to strengthen the scientific underpinnings of regulatory decision-making.