Case　retrieve　is　the　key　link　in　Case-Based　Reasoning(CBR)system,　and　the　distribution　of　attribute　weights　affects　the　retrieval　accuracy　directly.　However,　the　traditional　retrieval　methods　do　not　pay　much　attention　to　the　weights　distribution　which　led　to　low　retrieval　efficiency.　In　this　paper,　a　new　method　based　on　Water-Filling　principle　in　wireless　communication　field　is　proposed　to　optimize　the　case　attribute　weights.　Regarding　every　single　attribute　in　the　case　base　as　a　sub　channel,　then　calculates　the　importance　of　each　case　attribute　by　analyzing　the　data　volatility　with　the　Water-Filling　principle.　To　prove　the　availability　of　the　method,　a　glass　identification　dataset　from　the　UCI　database　is　used　for　a　simulation　experiment　and　the　result　illustrates　that　the　new　method　could　get　a　better　and　more　accurate　retrieval　result　compared　with　the　traditional　methods.　The　method　could　dig　the　inner　information　of　each　case　attribute,　and　could　assign　proper　weight　to　each　attribute,　which　improves　the　retrieval　accuracy　and　proves　that　the　method　the　paper　introduced　is　effective　for　CBR　system.