NOx emission standards are becoming stringiest over the world especially for heavy-duty vehicles. To comply with current and future regulations some vehicle manufacturers are adopting exhaust aftertreatment systems known as Selective Catalytic Reduction (SCR). The catalysts are based on Vanadium (Va) and the reductant agent based on ammonia. However, Va is listed on the California Proposition 65 List as potentially causing cancer and alternatives are being studied. This paper presents a model based on neural networks that integrated with a road vehicle simulator allows to estimate NOx emission factors for different powertrain configurations, along different driving conditions, and covering commercial, zeolite and mordenite alternatives as the base monolith for SCR. The research included the experimental study of copper based and iron based zeolites (ZSM5 and Cuban natural mordenite). The response of NOx conversion efficiency was monitored in a laboratory for varying space velocity, oxygen, sulfur, water, NOx and SO2 emulating the conditions of a Diesel engine exhaust along a trip. The experimental data was used for training neural networks and obtaining a mathematical correlation between the outputs and inputs of the SCR system. The developed correlation was integrated with ADVISOR road vehicle simulator to obtain NOx emission factors and to test each SCR system installed on light-duty and heavy-duty vehicles for standardized driving cycles and real measured driving cycles. Despite having lower NOx conversion efficiencies than the CATCO in the ETC/ESC and NEDC cycles, FeZSM5 maintain the Euro regulation level. Therefore FeZSM5 can be a possible candidate as far as pollutants regulation is considered.