Accurate monitoring of the charging and output of the refinery unit is required. These direct refineries need to provide a quick response to posts on crude oil compositions or directions to their latest request. Determining the physical properties of the intermediate products of the crude oil unit in the refinery based on conventional analytical methods requires time consuming and expensive processes. At this stage, multivariate calibration techniques, creating models that can replace conventional analysis methods and obtaining results using fast spectroscopic analysis. For this study, multivariate calibration techniques were used to determine the hydrocarbons in the naphtha product from crude oil distillation column. The results were evaluated by comparing with using the reference conventional method results. Parameters are Aromatics, Olefins, Benzene, Naphthenes, Paraffins, C7Plus (the sum of compounds with more than 7 carbons) and C6Minus (the sum of compounds with less than 6 carbons). Samples were analyzed by Fourier transform near infrared region spectroscopy between 10000 cm-1- 4000 cm-1 wavenumbers. Calibration models were obtained by partial least squares and genetic inverse least squares methods. Using these models, the relevant parameters for the validation set samples were estimated and compared statistically with the values of the reference analysis methods. The results has been indicated that parameters has been successfully modelled with R2 range from 0.917 to 0.998 for LSRN samples and R2 range from 0.963 to 0.996 for HSRN samples