Decision-makers often wish to have a quantitative basis for their decisions. However, there is often no ‘hard data’ for many important variables, which can paralyze decision-making processes or lead decision-makers to conclude that large research efforts are needed before a decision can be made. That is, many variables decision makers must consider cannot be precisely quantified, at least not without unreasonable effort. The major objective of (prescriptive) decision analysis is to support decision-making processes faced with this problem. The decisionSupport() function in the R package decisionSupport can be applied to conduct decision analysis. We provide a simple example (in annotated R code) of how the decisionSupport package can be used to inform a decision process. The example provided simulates the decision of forest managers to use controlled fires in conifer forests vs. running the risk of severe fire.