Monte-Carlo simulations are a well-established methodology to numerically assess the effect of variations of both mechanical and aerodynamic parameters on the aeroelastic stability of a suspended bridge. In this research paper we use this statistical approach to present a design methodology for the assessment of long span aeroelastic behavior that considers not only the flutter velocity as a unique safety index, as it is common practice, but also the trend of the total damping as a function of the wind velocity. Specifically, several significant in-service conditions are considered. Indeed, wind velocities at in-service conditions are events with a probability much higher than flutter condition, and in these cases a reliability analysis represents an added value in the design process. Therefore the statistical analysis of total damping at in service conditions is suggested as a useful tool to judge the performance of a structure especially for those structures where the wind-structure interaction represents the capital aspect of the overall design as it happens for the very long span bridges. Given the probability distribution of the input parameters, the Monte Carlo simulations allows one to statistically investigate the aeroelastic stability of the structure, in terms of range of variation of the total damping and flutter velocity, through an eigenvalue analysis. It is also possible to state the probability of not matching the design technical specification and the probability of being in a certain prescribed variation band. The mathematical and statistical background of the design methodology are presented and a case of study is analyzed with reference to the Messina Straits Bridge. The test case was chosen to stress the methodology with a challenging design, where extreme structural and aerodynamic solutions are implemented to reach a main span length of 3300 m and where the performances of the structure are deeply bounded to the reliability of the aeroelastic design. (C) 2014 Elsevier Ltd. All rights reserved.