Complex effect of sulphate(VI) ions on the continuous struvite (MgNH4PO4 6H2O, MAP) reaction crystallization process kinetics in DT MSMPR crystallizer and its final results was modeled numerically using artificial neural networks. Network was used as a multidimensional correlation between selected technological control process parameters (three inputs representing [SO4 2– ]RM: 0.05 – 1.0 mass %, pH: 9–11 and mean residence time: 900 – 3600 s) and 43 size–channels of struvite product CSD (43 outputs corresponding to L within the 5.0 10 –7 –1.8 10 –4 m range). Network model reproduces experimental, nonlinear lnn(L) data correctly and accurately. Presenting CSD in a form of population density distribution lnn(L) made direct theoretical insight and identification of potential various kinetic mechanisms dominating for required <[SO4 2– ]RM, pH, > vectors in various L ranges possible.