||This paper proposes a probabilistic-based method to produce liquefaction-induced ground failure maps so that hazard levels can be assessed for a large area, such as a county, township, or quadrangle. The method focuses on using probabilistic approaches to map estimates of liquefaction-induced lateral spread displacement, and defining the uncertainty associated with the displacement estimates. The proposed mapping method uses a newly developed empirical model for estimating quantities of lateral spread displacement, current probabilistic liquefaction triggering analyses, probabilistic strong ground motion estimates, surficial geologic maps, digital elevation models, and geotechnical data compiled into a spatial database. The proposed method accounts for variations in soil conditions, age, topography, spatial distribution, and major sources of uncertainty. Such major uncertainties include variability over space, lack of or poor quality data, and limitations of the empirical models to estimate liquefaction phenomena. The proposed mapping method accounts for these uncertainties by Monte Carlo random sampling. Soil type and thickness are important factors in estimating horizontal displacement from lateral spread. Thus, this paper presents a new empirical model for estimating the amount of lateral spread displacement based on these factors, along with other factors such as earthquake magnitude, distance to the seismic source, and topography. In addition, the paper discusses how cone penetration test (CPT) data can be used in conjunction with the proposed empirical model to estimate the amount of lateral spread displacement. To test its suitability and provide an example, the proposed mapping method is implemented to produce probabilistic liquefaction triggering and lateral spread displacement maps for a study area in Weber County, Utah. The new maps indicate substantial risk for liquefaction-induced ground failure in the study area during largemagnitude seismic events. This is because the study area is filled with potentially liquefiable sediments, nearly all subsurface explorations encountered shallow groundwater, and the study area is near the seismically active Wasatch fault zone. Large uncertainties in the mapped estimates leads to producing maps for 16th, 50th, and 84th percentile probabilities-enabling estimation of a distribution of probabilities.