The analysis and prediction of damage to buildings resting on highly compressible fine-grained ‘‘soft soils” containing (organic) clay and peat are key issues to be addressed for a proper management of subsidence-affected urban areas. Among the probabilistic approaches suggested in literature, those oriented to the generation of empirical fragility curves are particularly promising provided that a comprehensive dataset for both the subsidence-related intensity (SRI) parameters and the corresponding damage severity to buildings is available. Following this line of thought, in the present paper, a rich sample of more than seven hundred monitored (by remote sensing) and surveyed masonry buildings – mainly resting with their (shallow or piled) foundations on soft soils – is analysed in four urban areas of The Netherlands. Probabilistic functions in the form of fragility curves for building damage are retrieved for three different SRI parameters (i.e., differential settlement, rotation and deflection ratio) derived from the processing of Synthetic Aperture Radar (SAR) images by way of a differential interferometric (DInSAR) technique in combination with the severity levels of the damage recorded from the visual inspection of over 700 masonry buildings. As a novelty with respect to earlier similar studies, the work points out the methodological steps to be followed in order to identify the most appropriate SRI parameter among the selected ones. Thus, the objective of the paper is to improve the existing geotechnical forecasting tools for subsidence-affected urban areas, in order to target areas that require more detailed investigations/analyses and/or to select/prioritize foundation repairing/replacing measures.