The infection of the covid-19 fears the world population. As prevention strategies have not been developed, existing clinical approaches are only applicable to treat covid-19- positive individuals. Identifying the severity of the patient's illness is crucial for reducing the covid-19-related mortality rate. It is the pathology reports that are used as the foundation for determining the severity of the disease by the clinical specialists. However, a clinician's skill in making a diagnosis has a significant impact on how correct that diagnosis turns out to be. This manuscript described a supervised learning technique for performing computer-assisted covid-19 mortality scope using the pathology reports of the target patient. The experimental examination of the value of the suggested approach for anticipating mortality scope with few false alarms.