For many earthquake engineering applications, site response is estimated through empirical correlations with the time‐averaged shear‐wave velocity to 30 m depth (V_S30). These applications therefore depend on the availability of either site‐specific V_S30 measurements or V_S30 maps at local, regional, and global scales. Because V_S30 measurements are sparse, a proxy frequently is needed to estimate V_S30 at unsampled locations. We present a new V_S30 map for California, which accounts for observational constraints from multiple sources and spatial scales, such as geology, topography, and site‐specific V_S30measurements. We apply the geostatistical approach of regression kriging (RK) to combine these constraints for predicting V_S30. For the V_S30 trend, we start with geology‐based V_S30 values and identify two distinct trends between topographic gradient and the residuals from the geology V_S30 model. One trend applies to deep and fine Quaternary alluvium, whereas the second trend is slightly stronger and applies to Pleistocene sedimentary units. The RK framework ensures that the resulting map of California is locally refined to reflect the rapidly expanding database of V_S30 measurements throughout California. We compare the accuracy of the new mapping method to a previously developed map of V_S30 for California. We also illustrate the sensitivity of ground motions to the new V_S30 map by comparing real and scenario ShakeMaps with V_S30 values from our new map to those for existingV_S30 maps.