  As computer simulation methods have gained importance in more and more disciplines, the issue of their trustworthiness for generating new knowledge has grown, especially when simulations are expected to be counted as epistemic peers with experiments and traditional analytic theoretical methods. The relevant question is always whether or not the results of a particular computer simulation are accurate enough for their intended purpose. If a simulation is being used to forecast weather, does it predict the variables we are interested in to a degree of accuracy that is sufficient to meet the needs of its consumers? If a simulation of the atmosphere above a Midwestern plain is being used to understand the structure of a severe thunderstorm, do we have confidence that the structures in the flow—the ones that will play an explanatory role in our account of why the storm sometimes splits in two, or why it sometimes forms tornados—are being depicted accurately enough to support our confidence in the explanation? If a simulation is being used in engineering and design, are the predictions made by the simulation reliable enough to sanction a particular choice of design parameters, or to sanction our belief that a particular design of airplane wing will function? Assuming that the answer to these questions is sometimes “yes”, i.e. that these kinds of inferences are at least sometimes justified, the central philosophical question is: what justifies them? More generally, how can the claim that a simulation is good enough for its intended purpose be evaluated? These are the central questions of the epistemology of computer simulation (EOCS).