People who misunderstand risk are more likely to experience costly decision biases. In addition to serious personal and economic implications, risk misunderstanding can further undermine high-stakes risk mitigation efforts. What makes someone vulnerable to misunderstanding risk? Recent research suggests individual differences in statistical numeracy (i.e., ones’ practical probabilistic reasoning) tend to be the strongest predictor of general decision making skills and risk literacy—i.e., the ability to evaluate and understand risk (Cokely et al., 2012, 2018). The current study aims to develop some relatively straightforward and practical tools that provide insights and make meaningful inferences about who, when, how much, and why people may misunderstand risks (i.e., Decision Vulnerability Analyses). First, the development of a unidimensional measure of Risk Literacy lends itself to the development of numeracy norms and comparative risk literacy levels. Cumulative percentile rank norms are provided for the general public, as well as stratified by education, age, gender, and race. Next, a major potential threat is addressed: differential item functioning and measurement invariance. Results suggest that the Berlin Numeracy Test-Schwartz and the Risk Literacy Test pass strict measurement invariance, with good model fit (RMSEA < .06). Finally, a template for decision vulnerability analysis is developed and validated using five example artifacts (e.g., risk communications). Initial results suggest that over 90% of predicted risk literacy difficulty levels are within ten percentile points of the observed value. An additional out-of-sample application with hurricane risk communications is explored, and discussion focuses on theoretical implications, future research for methodological improvements, and further implications for high-stakes decision making.