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Accurate estimation of nutrients in the river and streams is very necessary for number of applications including determination of the sources of the nutrient loads in the watersheds, evaluating long-term trends in the loads, and estimating loading to downstream water bodies. As the measurement of the nutrient concentration in the stream is done on the weekly or monthly basis, there is need to estimate concentration and loads during the period when no data is available. The objectives of this study were to: (i) Document the performance of the multiple regression model to predict loads of nutrients in the Neuse River basin, and, (ii) Determine if there is any systematic bias in the load prediction. The LOADEST model is used to estimate riverine nutrient load. Data from five water quality station were used in this study and rating curves for total nitrogen, it derivative and total phosphorus were prepared. In this study LOADEST overestimated loading of most of the nutrients. Underpredicted cases consisted of water quality stations with small number of sampling data. Estimated total nitrogen varied from measured by -2% to 9% but for total phosphorus the value ranged -2% to 27%. One consistent pattern found (except the case of total nitrogen) was between the numbers of monitoring samples versus the magnitude of loading per unit area: lower the number higher the value of loading per unit area.