The objective of this work is to provide accurate and realistic characterization of different types of asphalt concrete mixtures using advanced material modeling within a probabilistic framework. The methodology adopted builds on and enhances a Viscoelastoplastic Continuum Damage (VEPCD) material model by utilizing a suite of associated experimental testing protocols and incorporating the uncertainties associated with the different material properties. The modeled uncertainties address the variabilities and errors associated with the Linear Viscoelastic (LVE) functions achieved from the complex modulus test and damage characteristic curves obtained from constant crosshead rate testing. A probablistic scheme using First Order approximations and Monte Carlo simulations is developed to characterize the inherent uncertainty of each of the LVE functions (dynamic modulus |E*|, relaxation modulus E(t), and creep compliance D(t)) over the time domain of their mastercurves. For damage characteristic curves, the uncertainty in normalized pseudostiffness (C) increases as the level of damage (S) becomes larger. This uncertainty, quantified by the coefficient of variability, does not exceed a value of 0.2 for a drop of C from 1 to 0.5. The conducted analysis shows that the uncertainty in C can be modeled directly as a function of the input stress without the need of developing two distinct models for C versus S and S versus stress. The uncertainties of LVE properties are propagated along with those of C versus stress curves to yield a probabilistic viscoelastic continuum damage model (P-VECD). The P-VECD not only predicts the average viscoelastic response to a given loading input, but it can also provide its distribution, which is essential for a reliability-based pavement design.