  This paper introduces and defends an account of model-based science that I
dub model pluralism. I argue that despite a growing awareness in the philosophy
of science literature of the multiplicity, diversity, and richness of models
and modeling-practices, more radical conclusions follow from this recognition
than have previously been inferred. Going against the tendency within the
literature to generalize from single models, I explicate and defend the
following two core theses: (i) any successful analysis of models must target
sets of models, their multiplicity of functions within science, and their
scientific context and history and (ii) for almost any aspect x of phenomenon
y, scientists require multiple models to achieve scientific goal z.
