The need for rapid crop fertilization is pronounced in a growing and changing world. With the continuous advancement in imaging resolution of multispectral cameras and the growing sophistication of spectral analysis software, spectral analysis technology has been increasingly adopted in agricultural production. This paper introduces to readers a research method that determines crop growth conditions by analyzing spectral images of cultivated areas and calculating vegetation indices (NDVI and NDRE values) of the planting regions. By integrating canopy spectral data with quantitative relationships between fertilization rates and crop yield, the approach provides scientific fertilization recommendations for different growth stages. Case analysis demonstrates significant positive correlations between NDVI/NDRE values and nitrogen application rates in drip-irrigated winter wheat. Specifically, NDVI exhibits stronger linear relationships with nitrogen levels during the reviving and flowering stages, while NDRE shows superior performance from stem elongation to ripening stages (stem elongation, leaf development, kernel development, and ripening). Based on the findings of this study, it can be confirmed that NDVI and NDRE indices obtained from imagery can effectively predict and analyze crop nitrogen status. Furthermore, this method is adaptable to other crops (e.g., corn, soybeans) and the UAV-mounted multispectral cameras enable large-scale optical image acquisition. Researchers could subsequently develop localized fertilizer recommendation software tailored to regional cultivation conditions, thereby establishing a comprehensive technical system encompassing fertilization monitoring and precision control—providing robust technical support for precision agriculture.