One of the main challenges associated with utilisation of the renewable energy is the need for energy storage to handle its intermittent nature. Power-toGas (PtG) represents a promising option to foster the conversion of renewable electricity into energy carriers that may attend electrical, thermal, or mechanical needs on-demand. This work aimed to incorporate a stochastic approach (Artificial Neural Network combined with Monte Carlo simulations) into the thermodynamic and economic analysis of the PtG process hybridized with an oxy-fuel boiler (modelled in Aspen Plus ®). Such approach generated probability density curves for the key techno-economic performance indicators of the PtG process. Results showed that the mean utilisation of electricity from RES, accounting for the chemical energy in SNG and heat from methanators, reached 62.6%. Besides, the probability that the discounted cash flow is positive was estimated to be only 13.4%, under the set of conditions considered in the work. This work also showed that in order to make the mean net present value positive, subsidies of 68 V/MW el h are required (with respect to the electricity consumed by PtG process from RES). This figure is similar to the financial aids received by other technologies in the current economic environment.