Aviation accounts for around 12% of all CO2 emissions from the transport sector, necessitating the use of sustainable aviation fuels. Electrofuels, which are gained from renewable sources, are attractive options for sustainable aviation fuels. Model-based electrochemical process design and optimization could very well assist in improved design and operation methods towards better conversion, selectivity, energy conversion, and economics - at a lower cost and time than the experimental approach. Moreover, nowadays, process models are also an indispensable technology for realizing Industry 4.0 and digital twin ideas for process intensification and monitoring. Thus, to design better electrofuel manufacturing processes and create digital process representations, this paper makes use of a first-principles model for electroreduction of furfural to furfuryl alcohol and methylfuran as well as hydrogen evolution. In detail, the Volmer reaction forms adsorbed hydrogen, represented by a Frumkin type isotherm. The hydrogen evolution is described by the potential dependent Heyvrosky reaction and the potential independent Tafel reaction. We critically discuss the simulation results using a global parameter sensitivity study and show its potential application for an AI-assisted process optimization strategy, i.e., predicting an optimal potential profile using the derived first-principle model and a neural network.