Deciding which areas to protect, and where to manage and how, are no easy tasks. Many protected areas were established opportunistically under strong political and economic constraints, which may have resulted in inefficient and ineffective conservation. Systematic conservation planning has helped us move from ad-hoc decisions to a quantitative and transparent decision-making process, identifying conservation priorities that achieve explicit objectives in a cost-efficient manner. Here we use Finnish butterflies to illustrate different modeling approaches to address three different types of situations in conservation planning at three different spatial scales. First, we employ species distribution models at the national scale to construct a conservation priority map for 91 species at the resolution of 10×10 km. Species distribution models interpolate sparse occurrence data to infer variation in habitat suitability and to predict species responses to habitat loss, management actions and climate change. Second, at the regional scale we select the optimal management plan to protect a set of habitat specialist species. And third, at the landscape scale, we use a metapopulation approach to manage a network of habitat patches for long-term persistence of a single butterfly species. These different modeling approaches illustrate trade-offs between complexity and tractability and between generality and precision. General correlation-based models are helpful to set priorities for multiple species at large spatial scales. More specific management questions at smaller scales require further data and more complex models. The vast numbers of insect species with diverse ecologies provide a source of information that has remained little used in systematic conservation planning.