Background:Many radiologists recognize that there are common lung nodules, that majority of them are benign, and that not all benign lung nodules need the same management.The Lung Imaging Reporting and Data System (Lung-RADS( was introduced to create a framework for the analysis of screen-detected nodules and to enable nodule management further standardized. Aim of work:To assess the performance of Lung-RADS in categorization of pulmonary nodules using baseline screening CT scans. Subjects and methods:A prospective comparative study was conducted in radiodiagnosis department, Zagazig university hospitals on 30 patients referred from the chest department of Zagazig university hospitals as well as the outpatient clinics for CT lung screening during the period from August 2018 to May 2019.All patients were subjected to complete history taking, full clinical examination, MDCT imaging, PET/CT imaging in some nodules, pathological examination, clinical and imaging follow up according to the criteria of the nodules after 6 months by CT. Results:Considering only those cases classified as Lung-RADS4X for predicting malignancy, the Lung-RADS had an accuracy, sensitivity, specificity, PPV, and NPV of 76.7%, 70.6%,84.6%, 85.7%, and 68.6%, respectively. Considering Lung-RADS4A, Lung-RADS4B and Lung-RADS4X together as predictors for malignancy, the accuracy, sensitivity, specificity, PPV, and NPV were 90%, 94.1%, 84.6%, 88.9%, and 91.7%, respectively.Conclusion:The LUNG–RAD classification method is a useful conceptualising system that aids in the classification, follow-up, and improvement of the prognosis of malignant pulmonary nodules.