Although　waste　incineration　is　a　promising　disposal　method,　it　produces　unwanted　combustion　by-products,　such　as　toxic　dioxins,　that　can　be　unintentionally　emitted.　Kitchen　scraps　can　result　in　incomplete　combustion　of　waste,　which　accelerates　the　formation　of　dioxins,　especially　for　the　small-sized　incinerators　without　identical　operating　temperature.　Consequently,　garbage　classification　before　waste　incineration　is　critical　for　dioxin　control　in　the　small-sized　waste　incineration　industries.　To　date,　the　influence　of　garbage　classification　on　dioxin　emissions　has　not　been　quantified.　In　this　study,　a　model　framework　integrating　the　grey　prediction　model　and　autoregressive　prediction　model　was　established　and　used　to　predict　future　dioxin　emissions　from　small-sized　waste　incineration.　If　garbage　classification　is　ideally　strictly　implemented,　annual　dioxin　emissions　could　be　reduced　by　up　to　1697　g　TEQ　over　the　next　10　years.　Garbage　classification　reduced　emissions　by　about　30.7%　compared　with　incineration　of　mixed　municipal　solid　waste　without　classification　(5534　g　TEQ　over　the　next　10　years).　The　established　model　framework　can　effectively　assess　the　influence　of　garbage　classification　on　dioxin　emissions　from　waste　incineration,　which　could　facilitate　the　widespread　adoption　of　garbage　classification.