Data envelopment analysis (DEA) is a methodology for identifying efficient frontier of decision making units (DMUs) with multiple outputs and inputs. Context-dependent DEA refers to a DEA approach where a set of DMUs are evaluated against a particular evaluation context. Each evaluation context represents an efficient frontier composed by DMUs in a specific performance level. Context-dependent DEA measures the attractiveness and the progress for each DMU. Current paper extends the context-dependent DEA by ranking all units on the basis of attractiveness and progress measures. The method is applied to measure the attractiveness and progress of 49 bank branches, and ranking them with Context-dependent DEA.