Denitrification and leaching losses of Nitrogen (N) in maize production result from dynamic and complex interactions among weather, soil hydrology, crop water and N uptake, and management practices. Current tools for N management do not directly account for the dynamic behavior of soil N, limiting our ability to more efficiently manage N. The use of dynamic simulation models as nutrient management tools represents a major step forward in our ability to manage agricultural nutrient flows. In our current work, we developed the Precision Nitrogen Management or PNM model, composed of a dynamic simulation model of soil N transformations and soil N/water transport (LEACHN; Hutson, 2003) linked to a well-tested maize N uptake/growth model (Sinclair and Muchow, 1995). Our goal is to apply the PNM model to improve N use efficiency and reduce N losses in maize production. To achieve this goal, we are developing and testing two N management tools with the PNM model. First, a new Nitrate Leaching Index (NLI) for maize production is being constructed for the Northeast US. The new NLI is based on multi-year PNM model simulations using archived weather data and input files representing a range of soil types and management practices. We initially focused on timing/rate of manure applications for maize silage production where the range of the manure applications used in the simulations fell within current recommendations for New York State. Simulated yearly total N losses were high and variable (100 – 260 kg N ha^-1). This variability in total N losses was associated with management practice (up to 70 kg N ha^-1 lower N losses for spring vs. fall manure applications) and weather (year-to-year differences of up to 90 kg N ha^-1). Soil type affected the partitioning of N losses between leaching and denitrification but had little impact on total N loss in a given year. Simulated average annual N concentration in water draining out of the root zone was approximately 20 mg nitrate (NO₃)-N L^-1 and 15 mg NO₃-N L^-1 for fall and spring applications, respectively, consistent with measured data from maize silage production areas in New York State where current manure application guidelines are being followed. We are developing a new NLI by ranking the parameters in the input files according to their impact on annual average N concentration in water draining out of the root zone. This will allow for more dynamic assessments of management options to reduce NO₃-N leaching and total N losses while maximizing crop yields. The second application of the PNM model is the development of an N management tool for in-season N application guidelines. Recent data indicate that the economic optimum sidedress N rate varies by up to 60 – 80 kg N ha^-1 annually, largely as a result of variable early season weather. Current guidelines for in-season N applications don't account for this variability. Using the PNM model, we generated adjustments to the recommended in-season N rates for maize in the 2004 and 2005 growing seasons for different climate regions in New York State. Adjustments ranged from an increase of 30 kg N ha^-1 over the recommended rate in 2004 to a decrease of 25 kg N ha^-1 below the recommended rate for some climate regions in 2005. We are developing a Web-based version of this tool that will automatically access high resolution climate data (Northeast Regional Climate Center at Cornell University) and allow farm- or field-specific in-season N recommendations.