Idealizations are assumptions made without regard for whether they are true and often with full knowledge they are false. This book develops a strong view of idealization’s centrality to science and reconsiders the aims of science in light of that centrality. The starting point is well-accepted ideas about how science is shaped by its human practitioners and by the world's complexity. Together, these ideas inspire a view of science as the search for causal patterns, a search that relies significantly on idealizations. Idealizations contribute to science in a variety of ways, including by playing a positive representational role. Case studies from across science are used to demonstrate idealizations’ ubiquity in science, as well as the wide range of purposes they serve. This account of idealization has implications for central philosophical debates about the aims of science. First, it provides reason to think the epistemic aim of science is not truth but human understanding. Understanding is a cognitive achievement that, unlike truth, can be directly furthered by idealizations. This in turn motivates an account of scientific explanation that does justice to how the production of understanding depends on human cognizers, including the cognitive value of causal patterns. It also inspires a view of the relationship among scientific projects not as investigating discrete levels of organization, but as independent and partial explanations dependent on one another for epistemic support. Finally, this account of idealization expands the influence of human values on science's aims and products, while also constraining scientific and metaphysical pluralism.