Performance maps, which represent relations between performance and geometry parameters, are essential for engineers to make a first decision on preliminary specification of a product to be designed. However, actual design often needs to consider various performance and geometry parameters simultaneously. Therefore, the resulting performance maps must be constructed in a high-dimensional form. Based on these requirements, this paper proposes and demonstrates performance map construction with the aid of data mining techniques. Data mining can reveal characteristic patterns in high-dimensional data with performance and geometry parameters. Therefore, the data mining results make it easy to interpret complex features of performance vs. geometry relations, and help engineers to discover new knowledge for engineering design through interpretation. The present demonstration of a centrifugal diffuser demonstrated that the data mining techniques are suitable and applicable to high-dimensional performance map construction, together with actual acquisition of new knowledge for diffuser design that was unknown from conventional quasi-one-dimensional nozzle theory.