The credibility approach uses the ‘‘expected credits’’ of fuzzy variables to deal with the uncertainty in fuzzy objectives and fuzzy constraints. The approach transforms fuzzy Data Envelopment Analysis models into credibility programming-DEA models. Similar to the expected value approach to stochastic programming where random variables are replaced by their expected values, in the credibility programming-DEA (CP-DEA) model fuzzy variables are replaced by ‘‘expected credits,’’ which are derived by using credibility measures.