Nitrogen is an important component of chlorophyll and serves as a constituent element for various enzymes in plant photosynthesis. Traditional nitrogen content measurement is destructive, while solar-induced chlorophyll fluorescence (SIF) offers the possibility of directly detecting leaf nitrogen content from space. In this study, rice was chosen as the experimental subject. A model for estimating leaf nitrogen content was constructed based on canopy solar-induced chlorophyll fluorescence (SIF) data, vegetation physiological parameters, and canopy structural characteristics. The study also discussed the contribution of various indicator elements to the model at different growth stages. The results showed that (1)SIF and its indices, vegetation physiological parameters, and canopy structural values after flowering were smaller than before flowering, and the various indicators were influenced by temporal changes and nitrogen application control; (2) The best fit for the content of nitrogen based on mass (Nmass) was achieved with solar-induced chlorophyll fluorescence (SIF), chlorophyll content (Cab), and the fraction of SIF photons escaping from the canopy (fesc) (R2=0.675), indicating that SIF, Cab, and fesc can effectively indicate Nmass; (3) SIF was the most important indicator for estimating Nmass before flowering, while Cab and fesc were the most important indicators after flowering. Thus, phenology affects the estimation of leaf nitrogen content, a multi-angle model is needed for satellite-derived leaf nitrogen content. These findings can provide a basis for inferring regional cropland leaf nitrogen content and ecosystem productivity based on satellite-derived SIF.