According to various researches, one of main causes of flight accidents is human factors. It is important to collect and analyze event data in advance to minimize and prevent human errors by developing safety checklist. As a result, international aviation industry developed FOQA(Flight Operations Quality Assurance) for commercial airliners, and, upon its proven effectiveness, it is now highly recommended to adopt for all operations of aircraft. Therefore, this thesis studied fundamental Airport Risk factors identification Algorithm based on ICAO(International Civil Aviation Organization), SMS(Safety Management Systems) and Matrix. Airport Risk factors identification algorithm has been applied for methodology of this research and categorized by level of safety based on two factors: Probability and Severity. In addition, altitude, traffic volume, and actual Flight Operation history for various airports, runway, aircraft model with different time and weather condition were used as variable values. This study conducted regression analysis of ‘A’ organization’s flight event frequency and applied ICAO SMS Matrix to categorize the severity of the events according to international standards. Based on the analysis, derived from fundamental Airport Risk Identification Algorithm, which can be a proactive measure for safe operation. As a consequence, this study assessed the Airport safety level of each airport and drew a conclusion with countermeasures based on the problem found.