This article provides a concise overview of methods for analyzing policy choices that have been used in the study of long-term environmental challenges. We open with an overview of the broad classes of methods used for long-term policy analysis, and subsequent sections will describe in depth three particular methods. They are: statistical models, such as employed in the debate on the environmental Kuznets curve, which infer past patterns from data and project them into the future; robust decision-making, a decision analytic framework that supports choices under deep uncertainty, and relates near-term policy interventions to different clusters of long-term environmental futures; and adaptive control and agent-based modeling, which provide an approach to simulation modeling that focuses on cooperation and conflict among multiple actors and their choice of strategies. While all three approaches can be used for various applications, this article focuses on the challenge of a potential transition to a low-carbon future to illustrate the strengths, weaknesses, and synergies among the respective methods. In the final section, we offer guidance for choosing among methods.