The impact assessment phase of a comparative life cycle assessment (LCA) is essentially a multiple- attribute decision-making (MADM) problem. Alternative product systems are evaluated based on a number of environmental performance criteria . The competing systems are then ranked based on some aggregate merit index and, ultimately, the preferred alternative is selected. One particular aggregation algorithm is compromise programming, which generates a performance index based on mathematical distance From a specified ideal solution. A modified variant of compromise programming is proposed. This involves modifying the standard algorithm to allow far uncertain input data represented in possibilistic or fuzzy form. Since the resulting aggregated performance indices are also possibilistic, comparison of the alternatives is performed based on a simple fuzzy ranking rule. A numerical example is provided to demonstrate the use of the algorithm; the ranking results are compared with those generated using crisp and fuzzy versions of the PROMETHEE outranking method.