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Nitrogen (N) is a vital macro nutrient for plant growth. The adequate amount of this nutrient in rice paddy field is one of the key factors for generating optimum plant production. However, measuring soil N using conventional analysis takes time and expensive. Most of previous researches reported that near infrared spectroscopy (NIRS), which is rapid and inexpensive method, is able to successfully predict soil N due to its high correlation with soil carbon (C). The aim of this research is to test the ability of NIR technology to predict soil N content which is independently predicted from soil C of rice paddy field. Soil samples in 147 locations, including the coordinates, were collected from rice paddy field of Lombok Island, Indonesia. Parts of the samples were analysed in a laboratory using conventional analysis for total N and organic C, and other parts were scanned using near infrared spectroscopy (NIRS) for spectral data collection. A Partial Least Square Regression (PLSR) calibration model was developed using laboratory-analysed soil N (and C) data and soil spectral data. As the soil N and soil C have a poor correlation, but both can be predicted well using NIR technology, this means that the soil N was independently predicted from soil C using NIR technology. This shows that the NIR technology can be rapidly used to measure both soil total N and organic C, although both of them have low correlation.