Digital　Twin　(DT)　is　expected　to　boost　efficiency　and　save　cost,　for　manuscription,　system　optimization,　maintenance,　etc.　DT　realizes　this　via　experimenting　candidate　solutions　in　a　replica　of　physical　equipment　and　environment.　In　the　context　of　telecommunication,　Digital　Twin　Network　(DTN)　depicts　the　replica　of　physical　telecommunication　network.　However,　there　are　three　challenges　being　debated　most　for　DTN.　The　first　is　the　differentiated　requirements　during　stages　in　Network　Life　Cycle　(NLC),　and　these　requirements　drive　that　a　single　DTN　cannot　fit　in　the　stages　in　NLC.　The　second　is　the　decision　delay　from　DTN.　This　delay　makes　current　DTN　hard　to　be　utilized.　The　third　is　the　cost　on　full　functional　copying　physical　telecommunication　infrastructure　and　management　system.　Against　all　the　three　challenges　above,　the　Elastic　Digital　Twin　Network　Modeling　(EDiTNetMdl)　is　proposed　in　this　paper.　EdiTNetMdl　treats　DTN　modeling　in　hierarchy　and　levels　of　abstraction.　Class　and　inheritance　are　designed　for　representing　telecommunication　Network　Elements　(NE)　in　hierarchy.　NE　functions　and　connections　are　modeled　as　methods　in　Classes,　with　inheritance　hierarchy.　Full　data　acquisition　is　fulfilled　in　bottom　NE　instances,　well　abstract　metadata　and　function　description　is　provided　to　high　level　NE　and　connections.　The　reduced　processing　time　of　EdiTNetMdl　supports　more　flexibility　in　network　decision　making　with　prediction.　©　2023　IEEE.