The time‐averaged shear‐wave velocity in the upper 30 m () is widely used as a proxy for site characterization in building codes. Regional estimations of often use either slope‐based, terrain‐based, or geological approaches as a proxy. This technique has proven useful at a number of locations globally, and slope‐based estimates formed the basis of the original global model implemented by the U.S. Geological Survey. Geostatistical models involve the study of potentially spatially correlated parameters. Modeling challenges arise when parameters are scarce or uncertain, and traditional geostatistical workflows cannot be implemented in all settings. In this study, the benefits of the spatial extents of proxies are used to supplement local data to implement a methodology for improving estimates using a multi‐Gaussian Bayesian updating framework. This methodology is presented in the context of a data‐scarce region, specifically, the Kathmandu Valley in Nepal. Using geostatistical approaches typically used by the petroleum industry, this article develops a novel practice‐oriented framework for estimation that can be adapted for use on a region‐by‐region basis. This framework provides an informed estimate and assessment of the uncertainties in which quantification of is required in geotechnical earthquake engineering applications.