DOI: 10.2514/1.47118 Flutter is a destructive and potentially explosive phenomenon that is the result of the simultaneous interaction of aerodynamic, elastic, and inertial forces. The nature of flutter mandates that flutter flight testing be cautious and conservative. Because of this, further investigation of uncertainty analysis with respect to the flutter problem is desiredandwarranted.Predictionof flutterinthetransonicregimerequirescomputationallyexpensivehigh-fidelity simulation models. Because of the computational demands, traditional uncertainty analysis is not often applied to transonic flutter prediction, resulting in reduced confidence in the results. The work described herein is aimed at exploring various methods to reduce the existing computational time limitations of traditional uncertainty analysis. Specifically,thecouplingofdesignofexperimentandresponsesurfacemethodsandtheapplicationofanalysisare appliedtoavalidatedaeroelasticmodeloftheAGARD445.6wing.Fromahigh-fidelitynonlinearaeroelasticmodel, a linear reduced-order model is produced that captures the essential dynamic characteristics. Using reduced-order models, the design of experiment, response surface methods, and -analysis approaches are compared with traditional Monte Carlo-based stochastic simulation. All of these approaches to uncertainty analysis have advantages and drawbacks. Results from these methods and their robustness are compared and evaluated. HE potentially explosive nature of flutter mandates that flutter flight testing be cautious and conservative. The development of a flutterstabilityparameterwasundertakenfourdecadesagotogivea more reliable technique to predict the onset of flutter. Other methods of predicting flutter such as damping versus velocity are known to have a number of shortcomings, one of which can be the sudden degradationindampingasillustratedintheexplosive flutterexample shown in Zimmerman and Weissenburger [1]. In this classic paper, the flutter stability parameter was developed using the classical two-dimensional, two-degree-of-freedom (pitch/plunge) aeroelastic wing model, and the technique was shown to be applicable for higher-degree-of-freedom analysis. The flutter stability parameter (flutter margin) is calculated using the decay rate and damped frequency. Traditionally, computational aeroelasticity for loads and flutter prediction combines a linear finite element formulation for the structure with linear aerodynamic methods. At the same time, the prediction of aerodynamic performance and control surface effectivenessaccountsfortheeffectsofthestructuralelasticdeformations on the external aerodynamics by means of correction factors applied to results obtained when the aircraft is assumed to be rigid. Both practices are well-established in aircraft design and give accurate, reliable, and rather inexpensive predictions for static and dynamic