Background: Corona viruses: large family of viruses which can causes mild to severe respiratory diseases in human. Patient's profiles were combined and incidence of mortality was examined. However, there were limited studies and little evidence on clinical risk score of COID-19 patients’ in-hospital mortality in Ethiopia. This study aims to develop and validate mortality risk score in patients admitted to hospital. Objective: To predict risk of covid 19 mortality Covid 19 in patients admitted in Tibebe Ghion Specialized Teaching hospital covid 19 cares and treatment center: Bahir Dar University, Northwest Ethiopia, 2022. Method: Retrospective follow up study is conducted in Tibebe Ghion hospital from May 15/2022 to June15/2022.Using census approach 825 patients card were reviewed using structured checklist. Data was entered into Epi data, and exported to R. Descriptive statistics was computed and presented in tables and figures. Bivariable analysis was conducted and predictors with P- value <0.25 was retained for multivariable logistic regression. Covid 19 patient in hospital mortality prediction model was developed and its accuracy was checked by AUC and calibration plot, internally validated with 1000 bootstrap and clinical risk score was developed. Result: Incidence of mortality was 17.5%. Original model was developed AUC of 88.2%, accuracy 87.15, misclassification rate 12.85%, after validation it has corrected AUC of 86% and 0.0420 optimism coefficients. Decision curve analysis of the model has highest clinical and public health importance. Finally clinical risk score was developed with hypertension, diabetes mellitus, asthma, creatinine level, platelet count, cough, respiration rate, oxygen saturation, mechanical ventilation and covid 19 severities AUC 87.7%, sensitivity 81.2% and specificity of 82.4% at the threshold score of 3 and the model calibration test had a p-value of 0.3914. Conclusion and recommendation: New clinical risk score applicable for low and middle income countries were developed using easily available patient profile at admition. It may be helpful to identify patients who are and are not likely to die. Clinicians should use this risk score to stratify patients early based on their risk status and provide early treatment. Health care policy makers should incorporate this clinical tool in covid 19 care and treatment protocol. Key Words: risk, prediction, mortality risk score, covid 19, Tibebe Ghion hospital