Airport　terminals　have　rapidly　indoor　occupancy　flow　variations　and　complex　backgrounds.　Due　to　the　large　lag　of　air-conditioning　systems,　such　systems　have　difficulty　regulating　to　changes　in　indoor　loads,　resulting　in　untimely　control　actions,　poor　thermal　comfort　and　energy　waste.　To　address　this　challenge,　this　paper　takes　the　baggage　claim　hall　as　case　study,　and　proposes　a　model　predictive　control　strategy　based　on　dynamic　passenger　flow.　First,　the　model　predictive　control　strategy　of　air　conditioning　system　is　proposed,　and　the　dynamic　passenger　flow　is　introduced　into　the　predictive　control　to　realize　the　rapid　response　of　the　system　to　passenger　flow,　improve　indoor　comfort　level　and　reduce　the　energy　consumption　caused　by　the　conditional　PI　control　methods.　Moreover,　the　simulation　experiment　involving　air　conditioning　system　of　baggage　claim　hall　in　the　airport　terminal　is　carried　out　and　the　results　are　analyzed　in　typical　days　and　the　cooling　seasons.　The　simulation　results　show　that　the　model　predictive　control　strategy　based　on　dynamic　passenger　flow　proposed　in　this　paper　could　better　maintain　indoor　temperature　stability　and　faster　system　response,　and　save　13%　and　10%　energy　in　typical　days　and　cooling　seasons　respectively.　©　2023　IBPSA.All　rights　reserved.