With the development of industrialization, the problem of environmental pollution has become increasingly serious. Environmental monitoring data, as a measurement index of environmental quality, is increasingly valued by governments and citizens. However, the accumulated real-time monitoring data of the environment at current stage is mostly used to write basic reports, while the hidden laws or values still need to be further explored. This paper proposes two original environmental prediction models and conducts improvement on these two methods separately to predict the quality of the atmospheric environment. The following research results are obtained: the multivariate linear equation is optimized through stepwise linear regression, which can accurately predict the short-term atmospheric environmental quality; the improved BP neural network can predict the mid-term and long-term atmospheric environmental quality through short-term training.