Municipal　solid　waste　incineration　(MSWI)　is　essential　for　tackling　urban　environmental　challenges　and　facilitating　renewable　energy　recycling.　The　MSWI　process　has　characteristics　of　multiple　variables,　strong　coupling,　and　complex　nonlinearity,　requiring　advanced　process　control　(APC)　technology.　Although　there　have　been　several　reviews　on　the　modeling　and　control　of　the　MSWI　process,　there　is　a　lack　of　focus　on　model　predictive　control　(MPC),　a　widely　used　APC　technology.　This　article　aims　to　comprehensively　review　MPC　strategies　in　the　MSWI　process.　First,　it　describes　MSWI　process　technology　in　detail,　examining　control　issues　and　objectives　to　highlight　the　complexity　and　challenges　in　controller　design　while　providing　an　overview　of　MPC　methods　and　their　benefits.　Second,　it　reviews　incinerator　modeling　for　control,　including　traditional　modeling　techniques　and　machine　learning　technologies　such　as　fuzzy　neural　networks.　Third,　it　reviews　the　controllers　used　for　MSWI　process,　emphasizing　the　advantages　of　MPC　over　existing　control　methods.　Fourth,　it　discusses　the　current　status　of　MPC　design　and　online　updates,　covering　the　need　for　an　accurate　dynamic　predictive　model　and　objective　function　and　the　online　updates　components　such　as　predictive　modeling,　rolling　optimization,　and　feedback　correction.　Finally,　the　study　concludes　with　a　summary　of　the　findings.