Identifying a strategy for legacy software system evolution requires analysis and assessment activities. Information on performance and costs of software systems must be considered when making decisions on the most suitable strategy to be applied. Many approaches have been defined for supporting this task, and several authors have proposed decision frameworks for aiding the selection of evolution strategy. These approaches often lack of techniques for the management of uncertainty, traditionally considered as unscientific and as a source of errors and arising from the confidence of the answers provided by respondents. In this paper, an approach previously proposed is analyzed and extended with fuzzy logic concepts. The approach uses a measurement framework based on the Goal-Question-Metric (GQM) paradigm and a set of critiquing tables. Fuzzy logic principles have been introduced in both components, for obtaining a better insight of the analyzed software system quality and an indication of the risks to be assumed when one selected strategy is adopted instead of another.