The　mineral　flotation　process　is　a　complex　process　with　dynamics　and　uncertainties,　which　confronts　with　the　problems　of　accurate　soft　measurement　and　optimal　control　of　key　indices　such　as　concentration　grade　and　flotation　recovery.　With　the　advancement　of　relevant　technologies,　important　progresses　have　been　made　in　modeling,　control　and　optimization　of　mineral　flotation　process,　especially　in　the　data-driven　intelligent　methods.　The　research　progress　of　data-based　flotation　process　modeling,　control　and　optimization　methods　were　summarized.　First,　the　descriptions　of　the　flotation　progress　and　corresponding　control　problem　were　given　in　detail.　Second,　based　on　operating　data　and　froth　images,　working　condition　recognition　and　index　prediction　methods　were　summarized,　respectively.　Afterwards,　intelligent　control　strategies　were　introduced　from　the　perspectives　of　model-based　and　model-free　methods.　Then,　set-point　optimization　algorithms　with　single-objective　and　multi-objective　were　reviewed.　Finally,　future　tendencies　in　the　intelligent　control　of　the　flotation　process　were　discussed.　©　2023　Beijing　University　of　Technology.　All　rights　reserved.