Nitrogen (N), an essential element, is often limiting to plant growth.  There is great value in determining the optimum quantity and timing of N application to meet crop needs while minimizing losses.  Low nitrogen use efficiency (NUE) has been attributed to several factors including poor synchrony between N fertilizer and crop demand, unaccounted for spatial variability resulting in varying crop N needs, and temporal variances in crop N needs.  Applying a portion of the N fertilizer alongside the growing crop allows fertilizer availability to coincide more closely with the time in which the crop needs the most N and is expected to increase NUE.  This in-season application also allows for adjustments which can be responsive to actual field and weather conditions which result in varying N needs.  Simulation models have been identified as a precision management technique which has potential to maximize the synchrony of crop demand for N and fertilizer N supply.  The Maize-N model was developed to estimate economically optimum N fertilizer rates for maize by taking into account soil properties, indigenous soil N supply, local climatic conditions and yield potential, crop rotation, tillage and fertilizer formulation, application method and timing.  Strategies which detect crop N status at early growth stages can also improve NUE.  Active crop canopy sensors monitor the N status of the crop, allowing growers to make management decisions that are reactive to actual growing season conditions.  In a study conducted in 2012 and 2013, an active crop canopy sensor provided a normalized difference red edge index (NDRE) which was used to generate a sufficiency index (SI) for each plot.  The SI was then used in the modified algorithm developed by Holland and Schepers to determine an in-season N application rate.  Four replications of randomized complete blocks were conducted at each of 6 sites over a 3-state region including Missouri, Nebraska, and North Dakota.  The objective of this study was to evaluate these two approaches for determining in-season N rates: Maize-N model and an active crop canopy sensor.  Additionally, the study investigated effects of maize hybrid and population on the efficacy of the two N recommendation strategies.  The model-based and sensor-based approaches were evaluated for yield, nitrogen partial factor productivity, agronomic efficiency, and profitability.  For 10 of 12 site years, in-season N application rates for model-based treatments exceeded those of sensor-based treatments.  Additionally, sensor-based treatments had significantly higher nitrogen use efficiency as seen by partial factor productivity than model-based treatments for 10 out of 12 site years.  Given $5.00 corn prices and $0.50 fertilizer prices, profitability considering only N fertilizer costs was calculated.  The sensor-based approach was significantly more profitable than the model-based approach for two site years, and the model-based approach was significantly more profitable than the sensor-based approach for two site years.  Seven site years showed no significant difference in profitability between the sensor-based and model-based approaches.