Policymakers responsible for agriculture, rural economic growth, and food security worldwide are confronted by a myriad of climate-related risks. This chapter provides a framework for using climate information in the design of policy to manage such risks, highlighting several tools of analysis that can be applied in the context of both climate variability and global climate change. The concepts are developed through a case study of the rice sector in Indonesia, a country directly affected by climate variability related to El Niño-Southern Oscillation events. The risk assessment model is based on the probability of climate events, critical thresholds of damage related to those events, and the role of policy in reducing climate-related impacts on agricultural systems. Because risk assessment involves estimation of both the probability of climate events and the expected consequences of those climate events, Bayesian analysis is applied to show how climate information can be used to update subjective probabilities over short and long time scales. Bayesian updating can help reduce the chances that policymakers will make the wrong policy decision given all of the available information. Even with these tools, however, the chapter shows that there is always the chance for Type I and Type II errors in policymaking, because the climate system is impossible to predict with certainty.