Life Cycle Value Assessment (LCVA) is a decision making tool which considers environmental, economic and/or social aspects for the entire life cycle of a product or process from “cradle-to-grave”. LCVA can be used for a wide range of public policy and business decisions with the analysis being performed at various levels of rigour. By its nature, LCVA utilizes data sets of varying qualities drawn from a wide range of sources. The uncertainties in the input data obviously lead to uncertainties in the results of the LCVA analysis. To establish confidence in an LCVA's recommendations, it is important to consider these uncertainties and incorporate an assessment of uncertainty into the LCVA process. However, the diverse nature of the data sets being used makes it difficult to rigorously establish data uncertainty levels. In addition, the complexity of most life cycle models makes it difficult to trace uncertainty through the analysis process. What is needed is a pragmatic approach which can be applied to a wide range of LCVA projects. The approach must provide a means of 1) assessing data quality and uncertainty, 2) assessing the sensitivity of the LCVA recommendations to uncertainty of various input data sets, and 3) establishing the overall confidence of the LCVA recommendations.This paper presents a recommended methodology for assessing the uncertainty, sensitivity and quality of results from an LCVA. First, a method of qualitatively assessing data quality is described. Second, a method for combining data sets and estimating the resulting uncertainty is presented. Third, an example of calculating the sensitivity within an LCVA study is demonstrated. Finally, a method of establishing the overall confidence in the results of a life cycle value assessment is discussed. The methodology is illustrated using results of an LCVA being conducted on alternative automotive fuels. (SAE paper 980468  describes the automotive fuels LCVA in more detail.) The results show a broad uncertainty band for this particular LCVA which is based on a limited set of publicly available data.