Remote sensing for nitrogen management in cereal crops has been an intensive research area due to environmental concerns and economic realities of today’s agronomic system. In the search for improved nitrogen rate decisions, what approach is most often taken and are those approaches justified through scientific investigation? The objective of this presentation is to educate decision makers on how these algorithms are developed and evaluate how well they work in the field on a small-plot basis. A single approach for algorithm development will be discussed to allow individuals to experience what a researcher considers when constructing an algorithm. This particular presentation will ignore the spatial variability aspect of nitrogen management and focus primarily on temporal variability and the management of nitrogen from year to year and location to location. Several key algorithm components will be discussed including yield prediction, identifying in-season responsiveness, and ultimately deciding on a fertilizer rate. Finally, research results will be shared to show how well a single algorithm performs across a wide array of production environments.