Winter wheat (Triticum aestivum L.) is an important crop in Montana. Since 2015, the winter wheat breeding program has focused on improving Fusarium head blight (FHB) resistance in winter wheat. As part of the ongoing efforts, each year advanced lines in various stages of the breeding pipeline get evaluated in a misted nursery established at Southern Agricultural Research Center in Huntley, Montana. While manual disease scoring is still an important aspect of identifying disease severity in breeding lines, use of aerial phenotyping approaches is also being explored to evaluate the disease development and severity in the FHB nursery to increase precision. The objective of this study is to evaluate the potential of multispectral based aerial phenotyping to estimate FHB severity in winter wheat breeding lines. For this purpose, a M200 drone fitted with multispectral camera was utilized to collect data during the crop season-2024. The images were collected at different time points and heights viz. 10 ft, 33 ft. and 66 ft. While data is currently processing, the initial processed images indicated variations among in the breeding lines for disease severity, ranging from moderately resistant to highly susceptible, at visual level. We are using a hybrid approach utilizing both images and vegetative indices to train machine learning models for achieving high precision in the quantification of FHB severity.