Climate warming is leading to the erosion of Arctic permafrost coastlines at accelerating rates, with erosion up to 20 m yr^−1 along the Alaska Beaufort Sea. Yet, accurate predictions of this erosion require coupling thermal permafrost dynamics with coastal hydro-morphodynamics, and current models are either computationally prohibitive for long-term simulations or omit important physical processes. To address these issues, a new open-source Python-based model called Arctic-XBeach was developed to couple the morphodynamic model XBeach to a one-dimensional enthalpy-based thermal module. A focus of this first version of Arctic-XBeach is on thermal denudation, the dominant erosion mechanism at sites where elevated beaches limit direct wave–bluff contact. Unlike prior implementations of thermal modules coupled with morphodynamic models, ArcticXBeach uses an event-driven decoupling strategy. Specifically, the thermal module continues to calculate the evolution of the thawed layer during the year, but the morphodynamic module (XBeach) is only activated when simulated storms produce conditions under which thawed sediment is available for removal. Using this decoupled strategy results in a reduction of >99 % in the number of calculations required for each time step in comparison to continuous coupling of the two modules. Validation of the model was performed at Barter Island, Alaska. Observed temperature trends were well-reproduced by the model (RMSE < 1.5 K), and the modeled trends in shoreline & bluff recession matched the observed trends (RMSE of 2.0–4.1 m over evaluation periods spanning 2–3 years each, compared to a total observed retreat of ∼112 m over 70 years with peaks of 6.6 m yr^−1). Therefore, Arctic-XBeach has the potential to be used to run seasonal to decadal simulations of thermal- denudation dominated permafrost coastal changes, and also provides a flexible platform to integrate other Arctic-specific processes. Thermal abrasion and block-failure processes are planned as future extensions.