Normalized difference vegetation index (NDVI) may be very useful for turfgrass managers to measure turf quality and obtain an indirect measurement of turf N status. The objective of this research was to develop a Nitrogen Fertilization Optimization Algorithm (NFOA) for use in a turfgrass variable rate N applicator on bermudagrass [Cynodon dactylon (L.) Pers] fairways and creeping bentgrass (Agrostis stolonifera L.) greens in Oklahoma. Plots (0.9 X 1.5 m) were established in Stillwater, OK on a sand based ‘Crenshaw’ creeping bentgrass green and a Norge silt loam (fine-silty, mixed, active, thermic Udic Paleustolls) common bermudagrass fairway in a randomized complete block design with 10 replications. Treatments consisted of plots fertilized with 0, 12.2, 24.4, 36.6, 48.8, and 61 kg N ha^-1. Handheld GreenSeeker^TM sensors (NTech Industries Inc, Ukiah, CA) were used to obtain NDVI readings twice per month over two growing seasons. Multiple regression analysis (NDVI₁₄ = a + b₁R₁₄ + b₂NDVI₀) was performed where: NDVI₁₄ = NDVI of turf 14 d following fertilization (Target NDVI), a = intercept, b₁ = regression coefficient for N application rate, R₁₄ = N application rate in kg N ha^-1, b₂ = regression coefficient for NDVI prior to fertilization, and NDVI₀ = NDVI prior to fertilization (Current NDVI). Coefficients of determination for predicting N application rate for creeping bentgrass and common bermudagrass averaged r² = 0.78 and r² = 0.76, respectively and were highly significant (P <0.0001), positive relationships.