Various　tailings　storage　facility　(TSF)　failures　have　caused　catastrophic　consequences,　such　as　life　and　property　losses　and　environmental　destruction.　It　is　crucial　to　select　the　optimal　risk　reduction　scheme　(RRS)　to　guarantee　the　safety　and　stability　of　the　TSF.　Decision-making　problems　in　RRS　selection　for　TSF　failure　are　multiple-attribute　decision-making　problems.　During　the　RRS　selection　process,　the　psychological　behavior　of　the　decision　makers　should　be　considered.　To　solve　such　problems,　the　cloud-TODIM　(abbreviation　for　interactive　and　multi-attribute　decision-making　in　Portuguese)　method　is　proposed　for　RRS　selection　in　this　paper.　Firstly,　the　quantitative　evaluation　information　is　qualified　and　converted　into　clouds　based　on　the　cloud　model,　in　which　the　characteristics　of　fuzziness,　uncertainty,　and　randomness　can　be　described.　Secondly,　an　improved　TODIM　method　is　proposed　to　select　the　optimal　RRS.　Furthermore,　a　TSF　is　employed　as　a　case　study　to　examine　the　superiority　of　the　proposed　method.　Finally,　the　sensitivity　of　the　loss　aversion　coefficient　theta,　which　reflects　the　attitudes　of　the　decision　makers　(DMs)　to　the　loss,　is　analyzed　and　a　comparative　analysis　is　developed　therefore　illustrating　the　competitiveness　of　the　multiple-attribute　decision-making　of　the　proposed　method.