The quantitative assessment of flight risk under icing conditions was taken as the research object. Based on multifactor coupling modeling idea, the pilot-aircraft-environment coupling system was built. Considering the physical characteristics and randomness of aircraft icing, the extreme values of critical flight risk parameters were extracted by the Monte Carlo flight simulation experiment. The flight characteristics were studied comprehensively and heavy-tail characteristics and the distributions of different flight parameters were verified. Flight risk criterion was developed and one-dimensional extreme flight risk probability was calculated. Further, in order to solve the limitation of one-dimensional extreme value, with the Copula theory, the joint distribution model of flight parameters with three distinct distribution types was built. The optimal Copula model was selected by identification of unknown parameters and goodness of fit tests, and the three-dimensional extreme flight risk probability was defined. Based on the quantitative flight risk, the accident induction mechanism under icing conditions was discussed. Airspeed and roll angle under asymmetry icing conditions were more sensitive and had a more significant impact on flight safety. This method can provide reference for safety manipulation, boundary protection, and risk warning during icing flight.