Developing varieties adapted to dry conditions is one of the biggest targets for breeders. It is important to use inexpensive spectral sensing methods saving time in variety development. The aim of this study was to select bread wheat genotypes having high grain yield by using spectral sensing methods. Twenty-five bread wheat (Triticum aestivum L.) genotypes were evaluated under rainfed condition at three locations in Central Anatolia Region. The experiment was arranged in randomized complete block design with three replications. Grain yield (GY), Canopy Temperature (CT), Soil Plant Analysis Development (SPAD) and Normalized Difference Vegetation Index (NDVI) values were recorded. GY, CT, SPAD and NDVI were found to be statistically significant in terms of both genotype and environment. The relationship between grain yield and NDVI (R2=0.321**) values was linear. The positive correlation of GY (0.5671**) and SPAD (0.1729*) with NDVI suggest that NDVI can be used as efficient and precise selection criteria for identifying high effiency wheat varieties under rainfed conditions.