Summary: This paper discusses the new aspects of setting scale efficient targets in DEA with imprecise data such as ordinal and interval. The achieved models are nonlinear but it can be solved in linear Appa and Yue models with determining a set of exact data from imprecise input and output data. Numerical examples are provided to show the projection of DMUs to their most productive scale size under input minimization and output maximization criteria.