With the start of 2020, the world witnessed the spread of Coronavirus disease (COVID-19). We aim in this work to employ artificial intelligence (AI) to develop a computer-aided diagnosis system (CAD) in order to automatically detect COVID-19 cases and differentiate them from normal and community-acquired pneumonia (CAP) cases through the use of lung Computed Tomography (CT) images and then evaluate its performance. Deep residual learning offers a wide variety of algorithms that helps in classification problems. We apply in this work a ResNet50 based model to recognize Covid-19 cases. Extensive analysis based on an international dataset (24256 images of 304 patients) proved that the ResNet50-optimized model can recognize COVID-19 through the use of CT images with 82% accuracy, 90% recall, 65% precision, and 76% of F1.Score.