This paper describes the development of a software tool for automated analysis of interlaboratory comparison (ILC) results and verification of calibration scopes. The tool uses Python libraries to process.xls/.xlsx data files containing laboratory codes, measurement values, and associated uncertainties. The software implements algorithms for evaluating results using En and z statistical criteria. En values above 1 are marked as non-compliant, while z values are categorized as acceptable, doubtful, or non-compliant based on thresholds. To improve decision reliability, the program supports conformity assessment using seven different guard band strategies. Both binary and non-binary decision rules are included, enabling flexible risk-based evaluations. Graphical displays show measurement deviations, uncertainties, tolerance limits (TL), and acceptance limits (AL), with decision outcomes labeled for each case. Tabular results are also generated for clarity and reporting. The tool enhances accuracy and consistency in calibration assessment, helping reduce human error and decision-making time. It supports traceability and alignment with international metrological standards. This development addresses the growing need for digital solutions in modern calibration and ILC processes, contributing to quality assurance and improved performance in accredited laboratories.