Landslides are ubiquitous within the state of Oregon, imposing an annual estimated cost of more than $10 million. Weak, saturated soils at steep slopes combined with persistent rainfall throughout most of the year provide a dangerous environment for this natural disaster, particularly in western Oregon. This grim situation is intensified by the presence of the Cascadia Subduction Zone, which is capable of generating large and powerful earthquakes. This thesis presents a fully probabilistic method for regional seismically-induced landslide hazard analysis and mapping, which considers the most current predictions for strong ground motions and seismic sources through deaggregation of the USGS next generation attenuation (NGA) seismic hazard curves in conjunction with topographic, geologic, and other geospatial information. The landslide triggering analysis is integrated into the probability chain and performed using Newmark's sliding block method. In order to estimate strength parameters for each lithological unit, which are difficult to obtain in detail for such a large area, estimated friction angle histograms were derived for each unit based on the terrain slope at locations of previously mapped landslides within the unit. Next, predictive displacement regression models suitable for regional assessment were integrated into the probability chain to calculate the probability of exceedance for specific displacement thresholds (0.1, 0.3, 1.0, 10, 100 m) relevant to engineering and planning purposes. The landslide triggering probability map was validated by previously reported landslides (The Statewide Landslide Inventory Database of Oregon, SLIDO), where more than 99.8% of these landslides fall in "very high" category of hazard level on the landslide triggering map. The created maps are suitable for regional resilience and planning studies by various agencies as well as integration with other hazard maps for risk assessment. The maps can also be used to guide geotechnical investigation, but they should not be used in place of a site-specific analysis.