Edible coatings are recently gaining attention for potential applications in bakery products to extend the shelf life and incorporate functional characteristics, like probiotics, antimicrobial or an antioxidant compound, for which drying of the coating is an essential step. The aim of this work was to utilize near infrared (NIR) spectroscopy as a tool to rapidly monitor and develop predictive model for the drying of edible coating on bread (mini-burger buns) surfaces. The buns coated with edible coating were dried at two different temperature regimes, at 25 degrees C and 60 degrees C for one layer of coating and one temperature regime at 60 degrees C for two layers of coating. NIR spectra were collected and moisture content was determined at different drying times. The spectral data were pre-treated and subjected to Principal component analysis (PCA) for discrimination of drying times and subsequently to Partial least squares (PLS) regression for moisture prediction for given temperature, time and surface. Results show that NIR spectroscopy was able to reflect the drying process and discriminate between the various surfaces of bread and times of drying, primarily by the differences in water and protein absorption bands (1940 nm, 1500 nm, 2050 nm). Also, the subsequent PLS regression of the spectral data was found to describe satisfactorily the drying behaviour and the optimal drying moment with RMSE values 3% for the calibration and cross validation data sets. The procedure proposed could be used for faster quantification of moisture during drying process.