The increased use of engineered complex polymeric materials in the construction industry has highlighted their fire hazard. Screening of these materials, especially during the developmental stage, before safe commercial application requires standardized testing, which can be expensive. This research investigates the possibility of utilization of computational capability to predict fire hazard for facilitating screening of wall-lining materials in an important standardized configuration – a corner geometry without a ceiling. It also aims to fundamentally understand the dynamics of interactions between condensed-phase pyrolysis, gas-phase combustion, and flame heat feedback during concurrent, buoyancy-driven flame spread. Consequently, hierarchical experiments and modeling from small-scale to large-scale scenarios were performed using samples having mass in orders of magnitude between a milligram to a kilogram. Small-scale experimental data were inversely analyzed to develop comprehensive pyrolysis models using a hill-climbing optimization technique in a comprehensive pyrolysis solver, ThermaKin. Large-scale experiments performed over a non-charring, non-swelling material with well-characterized condensed-phase pyrolysis – Poly (methyl methacrylate) (PMMA) – provided valuable data for fast-response (13 s response) calorimetry, well-resolved flame heat feedback (maximum ± 6 kW m-2 error) at 28 locations, and radiation intensities at spectrally-resolved narrowband wavelength (900 ± 10 nm) corresponding to soot emissions during the flame spread. An empirical flame heat feedback model obtained from large-scale experiments conducted over PMMA was then coupled with the pyrolysis model to develop a low-cost semi-empirical model for simulating fire dynamics during flame spread. The hierarchical experiments and modeling framework was further applied to two important wall-lining materials, Polyisocyanurate foam and Oriented Strand Board, to scrutinize the robustness of the developed modeling framework. The study has presented a systematic methodology that predicted the fire dynamics in the large-scale tests over the three studied materials and can be judiciously extended to other materials. To further improve the large-scale modeling predictions, it is necessary a) to reduce the pyrolysis parameter and the flame heat feedback uncertainty below the minimum ±10% observed uncertainty, b) to quantify the convection-radiation contribution to the flame heat feedback, and c) to investigate the ability to generalize the empirical flame heat feedback model to other materials.