As the most mature denitration technology in the cement clinker burning process, selective non-catalytic reduction (SNCR) has been unable to meet the requirements of ultra-low nitrogen oxide (NOX) emissions under low ammonia escape, thus a hybrid denitration process based on SNCR was established. The process had three steps: reducing the NOX background concentration (NBC), implementing staged combustion, and optimizing the effect of the SNCR. One of the keys to this process was the real-time acquisition of the NBC. In this paper, a multivariate linear regression model for the prediction of NBC was constructed and applied to one 12,000 t/d production line and one 5000 t/d production line. For the 12,000 t/d production line, NBC had a positive correlation with the temperature of the calciner outlet, the pressure, and the temperature of the kiln hood, and it had a negative correlation with the quantity of the kiln coal, the temperature of the smoke chamber, and the main motor current of the kiln. The influence degree of each parameter on the NBC is gradually weakened according to the above order. The determination coefficient (R2) of the model was 0.771, and the mean absolute error and maximum relative error between the predicted and measured NBC were 6.300 mg/m3 and 18.670 mg/m3 respectively.