The　study　of　earth　movements　and　their　occurrence　factors　contributes　positively　to　the　reduction　of　damages　resulting　from　disasters　caused　by　landslides,　falls　or　alluvium.　The　investigation　of　early　warning　systems　for　landslide　events　that　is　developed　for　this　case　uses　main　variables　for　the　generation　of　movement.　In　this　case,　the　main　conditioning　factor　is　the　slope,　and　the　triggering　factor　is　the　precipitation,　measured　through　the　daily　precipitation　history　of　the　mountain　town　of　San　Jose　de　Maipo,　Chile.　Using　fuzzy　logic　rules,　an　algorithm　capable　of　establishing　logical　relationships　between　variables　with　a　prediction　accuracy　ratio　of　over　88%　is　developed,　which　implies　that　the　applied　model　is　efficient　at　the　time　of　detecting　a　real　warning　signal.　©　The　Author(s),　under　exclusive　license　to　Springer　Nature　Switzerland　AG　2024.