Computational Fluid Dynamics is a fundamental tool to simulate the flow field and the multi-physics nature of the phenomena involved in gas turbine combustors, supporting their design since the very preliminary phases. Standard steady state RANS turbulence models provide a reasonable prediction, despite some well-known limitations in reproducing the turbulent mixing in highly unsteady flows. Their affordable cost is ideal in the preliminary design steps, whereas, in the detailed phase of the design process, turbulence scale-resolving methods (such as LES or similar approaches) can be preferred to significantly improve the accuracy. Despite that, in dealing with multi-physics and multi-scale problems, as for Conjugate Heat Transfer (CHT) in presence of radiation, transient approaches are not always affordable and appropriate numerical treatments are necessary to properly account for the huge range of characteristics scales in space and time that occur when turbulence is resolved and heat conduction is simulated contextually. The present work describes an innovative methodology to perform CHT simulations accounting for multi-physics and multi-scale problems. Such methodology, named U-THERM3D, is applied for the metal temperature prediction of an annular aeroengine lean burn combustor. The theoretical formulations of the tool are described, together with its numerical implementation in the commercial CFD code ANSYS Fluent. The proposed approach is based on a time de-synchronization of the involved time dependent physics permitting to significantly speed up the calculation with respect to fully coupled strategy, preserving at the same time the effect of unsteady heat transfer on the final time averaged predicted metal temperature. The results of some preliminary assessment tests of its consistency and accuracy are reported before showing its exploitation on the real combustor. The results are compared against steady-state calculations and experimental data obtained by full annular tests at real scale conditions. The work confirms the importance of high-fidelity CFD approaches for the aerothermal prediction of liner metal temperature.