 A distinctive feature of the semantics of structural equations is that it encodes some notion of asymmetric determination. The values of the parent variables determine the value of the child variable, but not the other way around. Together with Halpern, Pearl devised several counterfactual analyses of causation in the framework of causal models. These analyses incorporate elements of the inferential approach to causation. To be more precise, condition AC2(a) of the original and the updated Halpern-Pearl definition of actual causality is counterfactual, while AC2(b) is inferential. The latter condition requires that a given effect must be a consequence of its cause for a range of background conditions. (See Halpern (2016) for details.) Notably, the framework of causal models has also been used to develop inferential approaches to causation that work without a counterfactual condition along the lines of Lewis (1973). We explain the basic concepts of the accounts by Beckers and Vennekens (2018) and Bochman (2018).