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A Custom made NIR spectroscope was used to determine the moisture content of in-shell peanuts of two different market type peanuts namely Virginia and Valencia. Peanuts were conditioned to different moisture levels between 6 and 26 % (wet basis). Samples from the different moisture levels were separated into two groups one for calibration and the other for validation. NIR absorption spectral data from 1000 nm to 2500 nm were collected on the peanuts from the calibration and validation groups. Measurements were obtained on 30 replicates within each moisture level. Reference moisture data were developed using standard air-oven method on calibration set samples. Partial Least Square (PLS) analysis was performed on the calibration set with certain pretreatments on the measured data and models were developed using the reference moisture data. The Standard Error of Calibration (SEC) and R2of the calibration models were computed to select the best calibration model for each of the two peanut types. Both Valencia and Virginia types gave R2of 0.99 for the pretreated as well as for the raw spectral data. The selected models were used to predict the moisture content of peanuts in the validation sample set. Predicted moisture contents of the validation samples were compared with their air-oven moisture values determined similarly as for the calibration samples. Goodness of fit was determined based on the lowest Standard Error of Prediction (SEP) and highest R2value obtained for the prediction models. The model, with reflectance plus normalization spectral data with an SEP of 0.74 for Valencia and 1.57 for Virginia type in-shell peanuts was selected as the best model. The corresponding R2 values were 0.98 for both peanut types.