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This paper describe a development of rice milling degree measurement system based on color analysis of rice sample. Rice Milling Degree is usually defined as the extent to which the bran layers of rice have been removed during the milling process. In Indonesia, rice quality is measured based on National Standard of Indonesia (SNI) of Milled Rice. Rice quality contains 11 variables resulting 5 categorizations of milled rice quality. Determination of rice quality is conducted manually by experienced inspector. This method has limitation in accuracy, objectivity and longtime measurement. This paper presents a measurement system of rice milling degree using image processing. Variety of IR-64 rice which 0%, 50%, 85%, 95% and 100% milling degree is used as sample and its image is taken using flatbed scanner. An RGB analysis then implemented to the sample and showed that the value of RGB is correlated with the value of rice milling degree in the sample. Adaptive Network Based Fuzzy Inference System (ANFIS) model then constructed using RGB value and normalized RGB value for better performance. Validation of ANFIS model using normalized RGB value resulting average error 3,55%.