Estimating crop nitrogen content is a critical step for optimizing nitrogen fertilizer application. The objective of this study was to evaluate the application of UAV images in estimating cotton (Gossypium hirsutum L.) N content. This study was conducted in a dryland cotton field in Garza County, Texas, in 2020. The experiment was implemented as a randomized complete block design with three N rates of 0, 34, and 67 kg N ha^-1. A RedEdge multispectral sensor was used to acquire multispectral images at four different growth stages. Plant samples were collected on the same days of image acquisition. N content of plant samples was determined using the combustion method. Empirical relationships between vegetation indices (VIs) and plant N content were developed for each multispectral image. The results suggest that UAV images have the potential to monitor the N content of dryland cotton.