[42] developed a nonlinear rate type viscoelastic model, by means of thermodynamic principles. A coupled temperature-dependent viscoelastic, viscoplastic, and viscodamage model was obtained by [PERSON] et al. [43], on the basis of a thermodynamic framework. Introducing the Helmholtz free energy and the concept of internal state variables, a viscoelastic-viscoplastic damage model, congruent from the thermodynamics point of view, was developed by [PERSON] and [PERSON] [44]. A deep discussion on the capacity of the model to reliably predict the volumetric deformation was provided; the contraction and dilation response of the material was successfully associated to the viscoelastic component and viscoplastic damage component, respectively. Within the ambit of thermomechanics, [PERSON] et al. [45] recently derived a constitutive formulation in finite strains and characterized by a viscoelastic dissipation potential to take into account the deviatoric and volumetric response, a modified Perzyna viscoplastic law with a non-associated flow rule, to model the inelastic deformation by means of a Drucker-Prager type plastic dissipation potential and a damage model, specifically introduced to represent the different behavior of the material in tension and compression. The environmental as well as the physical and chemical behaviors of the bituminous mixtures, related to ageing, healing, or moisture-induced damage, have also been introduced in some constitutive formulations [46; 47; 48; 49]. Other mathematical and numerical methods are based on fractional models [50; 51; 52; 53], rather than the distinct element method [54; 55; 56; 57]. The brief discussion just presented represents a partial overview of the total amount of studies conducted by different research groups on the modeling of asphalt concretes' behavior, based on the mechanics of materials. Nevertheless, it can be stated that the main and very important characteristic of such methods is the mechanistic framework of the numerical or mathematical expressions, which allows a rational analysis and deep understanding of the bituminous mixtures' response under different testing conditions. For this reason, the mechanistic constitutive methods also represent a really useful tool to support the mix design phase. Alternative approaches rely on methods that are not physically based, for instance, statistical rather than artificial neural networks (ANNs) models. Statistical regressions of experimental data sets could be an alternative approach to develop predictive equations of the HMA's property analyzed [58; 59; 60; 61]. Nevertheless, it has also been reported that ANNs can produce more accurate predictions with respect to multiple linear regression [62; 63]. Indeed, in recent years, ANNs have arisen in scientific research as a powerful numerical technique for data analysis [64], even in the pavement-engineering field. [PERSON] et al. [65] and [PERSON] et al. [66] verified the possibility of fitting Marshall test results of bituminous mixes to provide predictive equations that can be used to quicken the empirical Marshall mix design; nevertheless, such neural models are not mechanistically based and for this reason, they are considered as \"black box\" methods. However, the so called \"black box\" principle is basically based on a nonlinear fitting approach, as it has previously been widely discussed [66]. Furthermore, even without a physical basis, such approaches can be useful to reduce the number of laboratory tests required by the Marshall mix design, which is still widely adopted in many asphalt laboratories [67; 68; 69; 70; 71]. ANNs have also been used in other studies to model different mechanical parameters of bituminous mixtures for road pavement; such researches have reported the use of a basic network architecture, a standard approach for the data sampling and adoption of just one type of transfer function, namely the hyperbolic tangent one [65; 72; 73; 74; 75; 76; 77].