A　belief　Rule-base　Inference　Methodology　using　the　Evidential　Reasoning　approach　(RIMER)　has　been　developed　recently,　which　is　an　extension　of　traditional　rule　based　systems　and　is　capable　of　representing　more　complicated　causal　relationships　using　different　types　of　information　with　uncertainties.　A　rule-base　in　RIMER　is　designed　with　belief　degrees　embedded　in　all　possible　consequents　of　a　rule,　where　it　is　assumed　that　all　the　consequents　are　independent　of　each　other　in　order　to　accommodate　the　assumption　imposed　on　the　evidential　reasoning　(ER)　algorithm　being　used.　To　overcome　this　limitation,　in　the　paper,　we　extend　the　RIMER　approach　to　the　case　of　fuzzy　consequents,　that　is,　each　consequent　can　be　defined　as　a　fuzzy　linguistic　term　because　of　vagueness　and　inexactness.　In　such　cases,　the　intersection　of　adjacent　two　fizzy　sets　is　no　longer　an　empty　set,　which　results　in　the　above　ER　algorithm　inapplicable　during　the　inference　process,　instead,　the　inference　of　the　belief　rule-based　system　is　implemented　using　an　extended　fuzzy　ER　algorithm.　This　work　extends　the　applicality　and　feasibility　of　the　RIMER　approach.