Abstract: Runway bridges offer a practical structural solution for airport construction in terrain-constrained areas. However, their dynamic behavior under aircraft landing loads remains insufficiently studied, and design-oriented theoretical guidance is lacking. This study presents a novel analytical-numerical model for quantifying the dynamic load allowance (DLA) in runway bridges subjected to aircraft landing. The aircraft is modeled as a spatial six-degree-of-freedom system comprising three mass-spring-damper units, accounting for both pitch and roll motions. The runway bridge is represented by a spatial multi-beam Timoshenko beam system, where lateral coupling between beams is considered to reflect the lateral distribution of the main landing gears. An analytical model is established to quantify the midspan deflection and bending moment DLAs of the central beam in response to aircraft landing, accounting for multi-stage gear contact and aircraft-bridge dynamic coupling. The finite element method is adopted to solve the coupled model, and model validation is performed using field-measured quick access recorder (QAR) data. Parametric analyses indicate that vertical landing velocity and roll angle are the most influential factors governing DLA. Increasing vertical velocity from 0.5 to 2.5 m/s resulted in more than 260% growth in deflection DLA for short-span bridges, while a surface roughness transition from grade C to D amplified DLA by up to 78%. Roll angle induced asymmetric loading, raising deflection DLA by as much as 320%, particularly in shorter spans. In contrast, pitch angle reduced structural response, with deflection DLA decreasing by up to 20%. Horizontal speed exhibited a moderate, span-dependent influence. Roll angle and landing velocity are the main factors affecting DLAs, while horizontal speed has a moderate influence and other factors have minor effects under typical landing conditions. These results highlight the critical role of aircraft dynamics and surface conditions in determining dynamic amplification and confirm the effectiveness of the proposed model in capturing span-sensitive behavior.