This study presents the practical validation of a non-invasive methodology for assessing the structural vulnerability of historic masonry buildings, proposed in the previous paper by the authors (see Part 1 of this volume) and based on photogrammetric data obtained using Unmanned Aerial Vehicles (UAVs). The method is tested on nine buildings in the village of Bova in Calabria, Italy. A drone survey is conducted to acquire high-resolution nadir and oblique images, which are then processed using Structure-from-Motion (SfM) techniques to generate textured 3D models, orthophotos, and dense points clouds. Visually detectable parameters, selected as significant for structural vulnerability assessment, are extracted directly from the photogrammetric outputs and used as input for a structured, Excel-based tool. Analytic Hierarchy Process (AHP) is used to weight the parameters and Excel Visual Basic for Application (Excel-VBA), enables users to select responses for each parameter via dropdown menus. Internal automation then converts these selections into numerical scores. A vulnerability index is computed for each individual building, which is classified into three vulnerability levels.