Biofouling development on nanofiltration membranes treating tertiary effluents was studied at low (5. bar) and high (25. bar) pressures at different feedwater concentrations, temperatures and lengths of operation. The bacterial community profile composing the biofouling layer was characterized. Most of the bacterial species identified were Gram-negative, with Proteobacteria (approximately equally divided between β, α and γ subdivisions) and Bacteroidetes being the prevalent groups. At high-pressure, scaling was the primary source of fouling whereas at low-pressure, biofouling was dominant. For these conditions, an empirical approach to forecasting the contribution of biofouling resistance to total resistance was derived based on the resistance in series theory. This approach showed that biofouling becomes a dominating factor after approximately 20. L of permeate volume has been produced. A data-driven modeling algorithm for forecasting the reduction in permeate flux due to biofouling was also established. The reduction in permeate flux rates was related to the development of a fouling layer on the membrane. Pressure, total organic carbon, pH and conductivity of the feedwater were the most influential parameters. These results are novel in the area of model tree algorithms as they apply to forecasting the development of biofouling on membranes.