Suppose some event (E) occurred as a result of various causal factors. How do we determine the causal strength of a particular factor (C)? This talk will propose a measure of actual causal strength derived from a general hypothesis about how causal cognition works, involving probabilistic simulation of alternative counterfactual scenarios (i.e., scenarios involving C and E other than the one that in fact occurred). The resulting measure predicts some well-known and some surprising effects of probabilistic expectation in causal judgments. In addition, without any further additions or modifications to the account, we can easily explain effects of other varieties of norms, including moral and prescriptive norms. The discussion will conclude by considering the question of why it would be reasonable (e.g., from a functional point of view) for people to make causal judgments in this way.