In　order　to　design　the　structure　of　extreme　learning　machine(ELM),　a　pruning　algorithm　is　proposed　by　using　the　sensitivity　analysis　method.　The　residual　error＇s　sensitivities　to　the　hidden　nodes　are　defined　by　their　outputs　and　weight　vectors　connecting　to　the　output　layer.　The　model　scale　adaptability　is　calculated　and　the　hidden　nodes　are　sorted　by　using　the　defined　sensitivities.　Then,　the　number　of　requisite　hidden　nodes　is　estimated　by　the　model　scale　adaptability.　The　redundant　nodes　with　smaller　sensitivities　are　removed　from　the　existent　network.　The　simulation　results　show　that　the　proposed　approach　can　construct　the　compact　structure　for　ELM　effectively.