The paper presents a novel tool for the operational analysis of Renewable Energy Communities (RECs). With the application of random sampling methods and the utilization of historical energy metering databases, the tool is capable of predicting the energy behaviour of RECs of different size and composition, allowing to compute relevant technical and economic metrics while accounting for impactful correlation phenomena in the energy profiles of the REC members. The tool has been tested on a representative case study, performing energy profile estimation, sensitivity analyses and financial incentive assessment of a large-scale energy community.