The traditional framework for assessing alternative climate-changing policies, which shapes much climate-change policy research and informs the thinking of many of the most sophisticated policy-makers, rests on the assumption that we can predict the future. Climate change, however, presents a problem of deep uncertainty, where key aspects of the future remain unpredictable. Under such circumstances, policy-makers should seek strategies that are robust against a wide range of plausible scenarios. Such strategies are desirable because they would perform reasonably well, at least compared to the alternatives, even if confronted with surprises or catastrophes. Robust strategies may also provide a more solid basis for consensus on political action among stakeholders with different views of the future because it would provide reasonable outcomes no matter whose view proved correct. This paper describes novel analytic methods for finding robust strategies. These methods, called exploratory modeling, combine some of the best features of narrative scenario-based planning and quantitative decision analysis. The authors suggest that robust strategies for climate change are possible. In the near term, the key components of such strategies should include: establishing the physical and institutional capability to monitor the relevant climate and economic systems, establishing the capability to effectively regulate greenhouse gases, and encouraging the development and diffusion of new emissions-reducing technologies.