Thalassemia　is　an　inherited　blood　disorder　caused　by　abnormal　production　of　hemoglobin.　In　order　to　establish　an　efficient　thalassemia　prognosis　process,　the　practitioners　suggest　using　complete　blood　count　(CBC)　report.　Based　on　CBC　report,　practitioners　often　use　professional　experience　and　domain　knowledge　to　discover　the　cause　and　relevant　risk　factors.　Thus,　to　the　best　of　our　knowledge,　this　research　is　the　first　that　uses　machine　learning　techniques　to　accurately　classify　and　predict　thalassemia　patients　using　the　parameters　of　CBC　report.　WBC,　RBC,　HB,　HCT,　Platelets　and　an　additional　parameter　Ferritin　(Iron)　are　the　selected　parameters　for　the　experimentations.　The　experimental　analysis　of　the　results　show　that　RBC,　HB,　and　Ferritin　(Iron)　plays　a　vital　role　in　the　establishment　of　an　efficient　thalassemia　prognosis　process.　©　2020　IEEE.