The rapid advance of digital soil mapping (DSM) has resulted in the generation of fine resolution soils spatial datasets with associated uncertainty that can be as accurate but more cost-effective and faster to produce than conventional soil maps. There is documented and increasing interest by policy makers and end-users in moving from conventional soil mapping to DSM; however, the wider operational use of DSM depends on demonstrating the effectiveness of DSM in fulfilling user needs and requirements along with providing DSM products that can be easily used by non-specialists. In this study we used the Hydrology of Soil Types (HOST) classification scheme, which was devised to predict flows in ungauged catchments and is used by both the research and policy maker communities in the UK, as the exemplar for comparing the efficiency of HOST class maps produced using both DSM and conventional soil map approaches for predicting catchment hydrological response. The performance for hydrological predictions of a detailed (1:25,000 scale) polygon HOST class map and a HOST-DSM class map produced via spatial disaggregation was assessed by comparing Base Flow Index (BFI) calculated using HOST class proportions from both maps with BFI calculated using flow data from gauges in 39 selected catchments. Results showed that the disaggregated HOST-DSM class map gave similar or even better BFI predictions than the conventional polygon-based HOST class map, while also providing a better insight on spatial soil variability within map units and its effect on hydrological predictions. This study demonstrates the potential of DSM to produce soil hydrological maps that provide comparable or better baseflow predictions than maps produced using detailed and intensive soil surveying. The study results also suggest that translating DSM of classes to more easily interpretable mapping datasets and incorporating prediction uncertainty in the final DSM product, as in the case of BFI maps based on HOST-DSM classes, could help with facilitating the transition towards a wider operational use of DSM.