This work proposes a systematic technique to carry out a structural vulnerability assessment of historic masonry structures using Unmanned Aerial Vehicle (UAV) photogrammetry. The proposed approach aims to improve structural risk mitigation efforts in small historic towns by overcoming the limits of existing on-site approaches, which are often intrusive and resource expensive, by using drone-based image data to detect peculiar structural parameters. The proposed technique formalizes observable visual parameters in orthophotos and 3D models, transforming them into a decision support system. For this purpose, 23 parameters are considered, which are divided into four macro-categories. These parameters are borrowed from official Italian Civil Protection forms, adapting them for remote analysis. Weights to the parameters are assigned using the Analytic Hierarchy Process (AHP), which is guided by experts in pairwise comparisons. The approach is implemented in an Excel-Visual Basic Application (Excel-VBA) environment, allowing users to input visual data, calculate scores, and generate a vulnerability index ranging from 1.00 (low vulnerability) to 5.00 (high vulnerability) for each individual building. The index is then framed into three vulnerability classes. This method provides a scalable, non-invasive, and reproducible methodology for guiding early vulnerability mapping and prioritization, which is especially appropriate for ancient urban centers.