Key Performance Indicators, help an organization to define and measure the progress of organization toward organizational goals. Key Planned Performance Indicators (KPPI) are the tools for measure the progress of organization toward goals and strategic. Since the Decision Makers are concerned with these attributes and indices in uncertain environments, selection of these indices is a Multiple-Attribute Decision-Making problem. In the past, several methods such as the linear weighting methods, AHP, TOPSIS, Fuzzy Logic and Mathematical programming have been used to solve the indices selection problem. In this thesis, we give a new grey-based approach to deal with the indices selection problem with regards to organizational strategic plans. Firstly, the weights and ratings of strategic- base attributes for all alternatives are described by linguistic variables that can be expressed in grey numbers. Secondly, using a Grey Possibility Degree (GPD), the ranking order of all alternatives is determined. Finally, an example of indices selection for instruction and research department of IRIB is used to illustrate the proposed approach.