Excessive application of chemical fertilizers has caused a series of environmental problems, including environmental pollution. Quantitative estimation of a sustainable fertilizer recommendation rate is paramount for formulating fertilizer management strategies to improve productivity of low-yield regions and to prevent environmental damage. In this study, the database was drawn from 31 experimental sites in the main maize production region of Northeast China, during the period 2009 to 2013, to study the relationships between yield factors and nitrogen application rates, and to explore sustainable nitrogen (N) fertilizer recommendation rates based on analysis using the fertilizer response model. The fertilizer response model method is a technique that can provide effective performance predictions for the estimation of the optimum crop balanced fertilizer rates in varied agricultural regions. Results revealed that the average grain yield in treatment of N180 (the amount of nitrogen application rate was 90 kg ha −1
) was highest, and the yield increase rate ranged from 4.77% to 58.53%, with an average of 25.89%. The sequence of grain yields in each treatment receiving N fertilizer management from high to low was: N180 > N270 > N90 in all the regions. The agronomic efficiency for applied N in N90, N180, N270 treatments was 11.8, 10.8, and 4.6 kg kg −1
, respectively. The average optimum N fertilizer recommendation rate in Liaoning province was 180.4 kg ha −1
, and the predicted optimum yield ranged between 7908.7 and 12,153.9 kg ha −1
, with an average of 9699.1 kg ha −1
. The mean optimum N fertilizer recommendation rate in western (WL), central and southern (SCL), eastern (EL), and northern (NL) of Liaoning province were 184.2, 177.2, 163.5, and 192.5 kg ha −1
, and the average predicted optimum yields were 8785.3, 10,630.3, 9347, and 9942.4 kg ha −1
. This study analyzed the spatial distribution of optimum fertilizer recommendation rates and the corresponding theoretical yield based on a large database, which helped to develop effective and environment-friendly N management strategies for sustainable production systems.