Membrane Aerated Biofilm Reactors (MABR) are gaining more and more acceptance in the plethora of wastewater process intensification technologies. Mathematical modelling has contributed to show their feasibility in terms of reduced energy consumption and footprint. Nevertheless, most simulation studies published until now are still focused on analyzing MABR as single units and not fully integrated within the flow diagram of the water treatment plant (WWTP). In this paper, the prediction capabilities of an integrated modelling approach is tested using full-scale data from Ejby Mølle WWTP+MABR site (Odense, Denmark). Mass balances, data reconciliation methods, process simulation and the different evaluation criteria were used to adjust influent, effluent and process indicators. Results show 10 % mismatch between flow, COD, N and P predictions and measurements in different plant locations. Using the adopted hydraulic retention time (HRT), nitrogen load (NL), membrane surface area (MA) and oxygen transfer rate (OTR), it was possible to predict nitrification rates (NR) within the interquartile range. This has been done under two different MABR operational conditions: with (#S2) and without (#S1) external aeration (EA) in the bulk liquid. The model provides additional process insights about biofilm structure, substrate gradients, weak acid base chemistry and precipitation potential. More specifically, simulations suggest the potential undesirable effects of sulfate (SRB) and iron reducing bacteria (IRB) on both microbial activity and composition of the biofilm. The latter may have a strong impact on ammonium (NHx), sulfate (SOx) and ferrous ion (Fe+2) conversion processes. The change of operational strategy in the scenario analysis highlights that the denitrifying activity of phosphorus accumulating organisms (PAOs) can enhance nutrient removal in MABR tanks. In addition, it was possible to assess the chance of success (in terms of energetic cost of nitrogen removal) of adding several MABR units in one tank of the WWTP under study before full-scale implementation.