The purpose of this study is to investigate the issue of fuzzy measures acquisition. Fuzzy measures are considered as important tools in modeling the interaction between the criteria in multicriteria decision making. The acquisition of fuzzy measures is a complex issue due to high level of subjectivity involved in it. Some approaches suggest the use of past precedents to determine the fuzzy measures for a new decision problem. We are extending the state-of-art on this issue by proposing an approach using similarity-based reasoning. Our approach allows eliciting the fuzzy measures from the decision maker. We propose the use of Case-based reasoning as an implementation methodology to resolve the issue of fuzzy measure determination. Based on the experimental results, we found that the issue of subjectivity in fuzzy measure determination could be resolved by human involvement.