Are Probabilities Indispensable to the Design Inference?

After sketching the various probabilistic accounts of the design inference, including the Bayesian and Dembskian models, I make a stab at developing, in an admittedly crude form, a non-probabilistic model, based on a measure of ontological complexity, which, I conjecture, may more faithfully represent the design inference as found in such classical texts as Aquinas, Reid and Paley. I discuss the various pluses and minuses of probabilistic and non-probabilistic models, with reference to one important test case: inferring design from anthropic coincidences in the fundamental constants of physics.