In　order　to　quantitatively　analyze　the　relationship　between　electromagnetic　radiation　(EMR)　parameters　and　the　deformation　and　failure　of　tunnel　surrounding　rock,　and　improve　the　prediction　accuracy　of　tunnel　deformation,　the　correlation　between　EMR　parameters　and　tunnel　deformation　(including　deformation　amount　and　deformation　rate)　were　analyzed　by　correlation　analysis　method　based　on　219　sets　of　field　test　data　of　Zhongyi　Tunnel　on　Lixiang　Railway.　The　most　relevant　parameters　among　the　intensity,　pulse　and　energy　indexes　were　used　to　develop　the　new　multi-parameter　models　for　tunnel　deformation　amount　and　deformation　rate.　The　developed　model　was　verified　by　the　monitoring　data.　The　tunnel　deformation　amount　and　deformation　rate　after　excavation　were　predicted　by　the　developed　models　of　this　study.　The　results　showed　that:　1)　Among　the　EMR　intensity,　pulse　and　energy　indexes,　the　most　relevant　parameters　of　tunnel　deformation　amount　are　the　maximum　peak　events　of　EMR　intensity　in　total　events,　the　peak　events　which　exceeding　average　energy　in　total　events　and　pulse　number,　respectively.　Their　fluctuation　rate　are　the　most　relevant　parameters　of　the　tunnel　deformation　rate.　2)　The　three-parameter　PLSR　models　of　deformation　amount　and　deformation　rate　were　established　by　the　Partial　Least　Squares　Regression　(PLSR)　method.　The　correlation　coefficients　between　the　calculated　values　and　the　measured　values　of　tunnel　deformation　amount　and　deformation　rate　were　0.838　and　0.927,　respectively.　It　showed　the　effectiveness　of　these　proposed　models.　3)　According　to　the　field　application　results,　the　prediction　results　by　the　three-parameter　PLSR　models　of　this　study　were　closer　to　the　field　data　than　those　by　the　unitary　regression　models.　The　prediction　accuracy　of　the　proposed　models　was　more　stable.　In　practical　engineering,　the　multi-parameter　model　of　tunnel　deformation　should　be　established　by　integrating　the　intensity,　pulse　and　energy　indexes　of　EMR,　which　can　accurately　reflect　the　actual　deformation　law　of　tunnel　surrounding　rock　and　promote　the　field　application　of　EMR　technology　in　engineering　practice.　©　2023　Editorial　Department　of　Journal　of　Sichuan　University.　All　rights　reserved.