The　prediction　of　the　initial　stress　in　composites　is　essential　for　the　non-destructive　testing　(NDT)　and　structural　health　monitoring　(SHM)　of　carbon　fibre　reinforced　polymer　(CFRP).　This　paper　examines　the　potential　of　Lamb　waves　in　the　inverse　of　initial　stress　by　calculating　the　influence　of　initial　stress　on　the　dispersion　characteristics　of　Lamb　waves　propagating　in　multilayered　CFRP　laminates.　By　introducing　the　mechanics　of　incremental　deformation　into　the　linear　three-dimensional　elasticity　theory,　the　Legendre　orthogonal　polynomial　expansion　(LOPE)　method　is　used　to　mathematically　model　the　Lamb　wave　propagating　in　multilayered　CFRP　laminates　subjected　to　horizontal　and　vertical　homogeneous　initial　stresses.　Then,　a　three-hidden-layers　Feed　Forward　Deep　Neural　Network　(DNN)　with　Back　Propagation　(BP)　algorithm　is　constructed　to　invert　the　magnitude　and　di-rection　of　the　initial　stresses.　The　input　features　are　the　phase　velocities　of　fundamental　Lamb　wave　A0　mode　at　five　different　frequencies.　Both　training　and　testing　samples　are　obtained　by　LOPE　forward　calculation.　An　ablation　experiment　is　presented　to　compare　the　two　different　activation　functions.　Finally,　the　accuracy　of　the　inverse　is　verified　by　comparing　with　the　available　outcomes　of　LOPE　forward　calculation.