This paper describes a computational approach, based on the theory of causal ordering, for inferring causality from an acausal, formal description of a phenomena. Causal ordering an asymmetric relation among the variables in a self-contained equilibrium and dynamic structure, which seems reflect people’s intuitive notion of causal dependency relations among variables in a system. This paper extends the theory cover models consisting of mixture of dynamic and equilibrium equations. When people’s intuitive causal understanding of a situation is based on a mixed description, the causal ordering produced by the extension reflects this intuititve understanding better than that of an equilibrium description. The paper also discusses the view of a mixed model as an approximation to a completely dynamic model.