Remanufacturing　and　recycling　industry　has　developed　rapidly　in　recent　years　due　to　its　benefits　in　reducing　waste　and　protecting　the　environment.　However,　the　uncertain　environment　and　excessive　emission　during　production　become　two　main　obstacles　for　its　further　development.　In　this　paper,　a　green-oriented　bi-objective　disassembly　line　balancing　problem　with　stochastic　task　processing　times　is　studied.　The　objectives　are　to　minimize　the　total　line　configuration　cost　respecting　the　given　budget,　and　minimize　the　total　contaminant　emission,　respectively.　To　depict　stochastic　processing　times,　their　mean,　standard　deviation　and　change-rate　upper　bound　are　assumed　to　be　known　since　it　may　be　difficult　to　obtain　the　complete　historical　data.　For　the　problem,　a　bi-objective　model　with　chance　constraints　is　first　formulated,　which　is　further　approximated　into　a　linear　distribution-free　one.　To　solve　the　second　model,　an　efficient　epsilon-constraint　method　is　proposed　based　on　problem　analysis.　Finally,　a　fuzzy-logic-based　approach　is　applied　to　recommend　preferred　solutions　for　managers　according　to　their　perspectives.　The　solution　methods　are　first　examined　by　a　case　study,　then　by　247　benchmark-based　instances　and　randomly　generated　instances.　Experimental　results　indicate　the　efficiency　and　effectiveness　of　the　proposed　methods　for　solving　the　green-oriented　bi-objective　problem.