The　short-term　traffic　flow　prediction　is　of　great　importance　for　traffic　control　and　guidance.　This　paper　presents　an　approach　using　a　Sugeno　fuzzy　inference　system　whose　input　space　is　participated　by　a　Gaussian　mixture　model　and　parameters　are　estimated　by　the　least　square　estimation　method.　The　proposed　approach　was　evaluated　on　a　benchmark　problem　of　the　Mackey-Glass　time　series　and　the　collected　traffic　flow　data　via　a　comparison　made　with　one　of　well-known　methods.　The　experimental　results　indicate　the　proposed　method　is　effective　and　competent.　©　2005　-　2012　JATIT　&　LLS.　All　rights　reserved.