During curing, eventually, an amorphous molecular entity appears in the system, recognizable as an insoluble gel. It is suspended in the still-liquid part of the mixture, the sol, in which those polymers of lower molecular weights not yet attached to the gel are harbored. At the gel point, a network of covalent bonds appears spanning the entire mixture. The curing reaction, nonetheless, proceeds further because the network contains some still unreacted functionalities. Ideally, an almost fully cross-linked amorphous material is made, which, upon cooling below the transition temperature T g , appears as a solid glassy material used in applications. From the simulation perspective, modelling such a process, which may involve thousands of interacting sites in typical MD systems, is highly challenging. A rich variety of molecular modeling approaches has, however, been proposed. First attempts involved Monte Carlo techniques, based both on kinetic-theory differential equations and off-lattice direct simulations, in which the coordinates of reactive groups were stochastically distributed, with crosslinking proceeding according to the capture-sphere mechanism. Alternative attempts relied on linking together several copies of a single pre-constructed dendrimer-like oligomer. Later studies began to incorporate the ability to simulate cross-linking events using molecular dynamics (MD) with molecular mechanics (MM) based force fields. Such approaches have found widespread use and have proven to be an effective tool to explore the behavior of epoxy-resin networks at the molecular level and to derive physical properties such as glass transition temperature, coefficients of thermal expansion, and elastic moduli. Recently, some of these molecular dynamics approaches have been coupled to machine learning techniques in order to optimize the chemical composition of the epoxy network with respect to a set of desired material properties. Finally, in recent years reactive force fields started to be applied to the problem. Their advantage is an accurate parameterization of the underlying curing reactions, yet still an artificial energy boost is necessary to overcome the activation energies and to observe reactions at realistic temperatures and feasible time scales. A further problem of simulations with reactive force fields is still the limitation to small systems sizes, which prevents the reconstruction of macroscopic material properties.