Precision nitrogen (N) management requires real-time diagnosis of crop N status, and recommends N application rates accordingly. Nitrogen nutrition index (NNI) has been proposed as a better indicator of crop N status, but it is not suitable for practical applications, because it requires destructive plant sampling and time-consuming analysis of plant N concentration. There has been increasing interest in using remote sensing technology to non-destructively estimate NNI. The objective of this study was to determine how well an active canopy sensor could be used to estimate NNI of winter wheat (Triticumaestivum L.) in North China Plain, and develop prediction models of NNI using its spectral vegetation indices. A N rate experiment was conducted in Quzhou Experimental Station of China Agricultural University in Hebei Province in 2009/2010. GreenSeeker canopy sensor was used to collect canopy reflectance at different growth stages, and aboveground biomass of the scanned plants were collected and N concentration was determined. The results indicated that vegetation indices (normalized difference vegetation index, NDVI, and red vegetation index, RVI) were significantly related to NNI at different stages, with R2 being 0.63-0.91, and 0.62-0.87, respectively, except the early stage of Feekes 4. Response index (RI) calculated with NDVI (RI NDVI) or RVI (RIRVI) were significantly related to NNI across growth stages, with R2 being 0.73 and 0.70, respectively. This result implies that the NNI can be estimated in a rapid, cost-effective way using active canopy sensor. The RI is also a good indicator of winter wheat N status. The GreenSeeker active canopy sensor has a good potential for precision N management in North China Plains.