ABSTRACT Lebanon is a densely populated country crossed by major faults. Historical seismicity shows the potential of earthquakes with magnitudes >7, but large earthquakes have never been instrumentally recorded in Lebanon. Here, we propose a method to simulate near-fault broadband ground motions for a potential Mw 7 earthquake on the Yammouneh fault (YF)—the largest branch of the Dead Sea Transform fault that bisects Lebanon from north to south. First, we performed the first 3D tomography study of Lebanon using ambient noise correlation, which showed that Lebanon could be approximated by a 1D velocity structure for low-frequency (LF) ground-motion simulation purposes. Second, we generated suites of kinematic rupture models on the YF, accounting for heterogeneity of the rupture process, and uncertainty of the rupture velocity and hypocenter location. The radiated seismic energy was next propagated in the inferred 1D velocity model to obtain suites of LF ground motions (<1 Hz) at four hypothetical near-fault seismic stations. These LF simulations included the main features of near-fault ground motions, such as the impulsive character of ground velocity due to the rupture directivity or fling-step effects (so-called pulse-like ground motions). Third, to obtain broadband ground motions (up to 10 Hz), we proposed a hybrid technique that combined the simulated LF ground motions with high-frequency (HF) stochastic simulations, which were empirically calibrated using a worldwide database of near-fault recordings. Contrary to other hybrid approaches, in which the LF and HF motions are generally computed independently, the characteristics of stochastic HF ground motions were conditioned on those of LF ground motions (namely on the characteristics of the velocity pulse, if it existed, or on the absence of a pulse). The simulated peak ground accelerations were in agreement with the ones reported in the Next Generation Attenuation-West2 (NGA-West2) database for similar magnitude and distances and with three NGA-West2 ground-motion prediction equations.