Data-mining methods using hierarchical and non-hierarchical clustering are proposed that will help engineers determine appropriate drilling conditions. We have constructed a system that uses clustering techniques and tool catalog data to support the determination of drilling conditions for printed wiring boards (PWBs). Variable cluster analysis and the K-means method were used together to identify tool shape parameters that have a linear relationship with the drilling conditions listed in the catalogs. The response surface method and significant tool shape parameters obtained by clustering were used to derive drilling condition decision equations, which were used to determine the indicative drilling conditions for PWBs. Comparison of the conditions recommended by toolmakers demonstrated that our proposed system can be used to determine the drilling condition for PWBs. We carried out the drilling experiments in accordance with the catalog conditions and mining conditions, and estimated the board temperature around a drilled hole, the drilling forces, and the roughness of the drilled hole wall.