In this BA dissertation, I deploy examples of non-causal explanations of physical phenomena as evidence against the view that causal models of explanation can fully account for explanatory practices in science. I begin by discussing the problems faced by Hempel’s models and the causal models built to replace them. I then offer three everyday examples of non-causal explanation, citing sticks, pilots and apples. I suggest a general form for such explanations, under which they can be phrased as inductive-statistical arguments incorporating (...) plausible assumptions. I then show the applicability of this form to explanatory practices in thermal physics. I explore the possibility that population genetics provides a similar form of explanation, and offer a novel defence of the statistical interpretation of population genetics proposed by Matthen and Ariew (2002). I close with remarks concerning how, when faced with competing causal and non-causal explanations of the same phenomenon, we can perform an Inference to the Best Explanation. (shrink)