To　achieve　better　classification　performance　using　case-based　reasoning　classifiers,　we　propose　a　retrieval-based　revision　method　with　trustworthiness　evaluation　for　problem　solving.　An　improved　case　evaluation　method　is　employed　to　evaluate　the　trustworthiness　of　the　suggested　solution　after　the　reuse　step,　which　will　divide　the　target　cases　and　its　suggested　solutions　into　a　trustworthy　set　and　an　untrustworthy　set　in　accordance　with　a　threshold　value　of　trustworthiness.　The　attribute　weights　are　adjusted　by　running　a　genetic　algorithm　and　are　used　in　the　second　round　of　retrieval　of　the　untrustworthy　set　to　obtain　the　classification　results.　Experimental　results　demonstrate　that　our　proposed　method　performs　favorably　compared　with　other　methods.　Also,　the　proposed　method　has　less　computation　complexity　for　the　trustworthiness　evaluation,　and　enhances　understanding　on　thinking　and　inference　for　case-based　reasoning　classifiers.　©　2015　Elsevier　Ltd.　All　rights　reserved.