Here we demonstrate the use of a probabilistic approach for quantifying soil physical properties and variability using time and environmental input. We applied this approach to a synthesis of soil chronosequences, i.e., soils that change with time. The model effectively predicted clay content across the soil chronosequences and for soils in complex terrain using soil depth as a proxy for hill slope. This model represents the first attempt to model soils from a probabilistic viewpoint.