Excess nitrogen applied to fields not only causes environmental pollution, but also results in economic loss for farmers. This thesis applied statistical methods to analyze and explain space-time patterns of crop yield and nitrogen use efficiency (NUE) in China at two spatial scales (province and county). Results showed substantial temporal and spatial variation of nitrogen use efficiency and crop yield. Soil, crop and climatic covariates were important explanatory variables of NUE, while economic variables and agricultural management practices were also important for crop production. The random forest model had a superior performance over the stepwise multiple linear regression model, because it captures non-linear relationships. Considering the uncertainty contributions of input data and models for NUE prediction, the government is encouraged to standardize the data collection process and inspire scientists to explore available data better using statistical tools and develop more suitable models.