Cutterhead　torque　is　a　key　operational　parameter　for　earth　pressure　balance　(EPB)　TBM　tunneling　in　soil　strata.　The　effective　management　of　cutterhead　torque　can　significantly　maintain　face　stability　and　ensure　the　tunneling　machine　operates　steadily.　The　Shenzhen　Metro　Line　12　project　at　Shasan　Station　utilized　the　world＇s　largest　rectangular　pipe　jacking　machine　for　constructing　the　subway　station.　This　project　has　enabled　the　collection　of　relevant　data　to　analyze　the　factors　influencing　cutterhead　torque　and　to　establish　a　predictive　model.　The　data　encompass　an　abundant　array　of　cutterhead　design　parameters,　operational　parameters,　properties　of　the　excavated　soil,　and　environmental　factors,　revealing　the　distribution　characteristics　of　cutterhead　torque　during　tunneling.　The　correlation　between　various　factors　and　cutterhead　torque　has　been　examined.　By　employing　multiple　regression　analysis　and　a　Levenberg-Marquardt　(L-M)　algorithm-based　neural　network,　an　optimal　prediction　model　for　EPB　cutterhead　torque　has　been　developed.　This　prediction　model　incorporates　various　factors,　including　cutterhead　diameter,　RPM,　soil　chamber　pressure,　soil　shear　strength,　and　the　soil　consistency　index.　And　the　degree　of　influence　of　each　factor　on　the　cutter　torque　was　also　revealed.　The　prediction　results　demonstrated　good　accuracy　compared　to　previous　models,　providing　valuable　insights　and　guidance　for　EPB　TBMs　or　pipe　jacking　machines　operating　in　soil　strata.　The　current　limitations　of　this　model　and　suggestions　for　future　work　have　also　been　addressed.