NIR spectroscopy combined with chemometric methods has been used to develop a prediction models of the most influential parameters in curing process of two types of hams (140 hams) using different salting techniques, lean hams salted on a tray and fatty hams in a tub, in which sodium is partially replaced. Spectral data were examined by principal component analysis and cross-validated calibration equations were developed using partial-least squares regression. Calibration errors for each parameter, obtained from cross validation (RMSECV), were similar to those obtained by reference method. For lean and fatty hams the RMSECV values were: Moisture 0.78% and 0.80; Fat 2.5 and 1.2%; Protein 0.7 and 1.7%; water activity 0.008 and 0.006; Proteolysis Index 1.6 and 1.7%; Sodium 0.11 and 0.10%; and Potassium 0.04 and 0.10. Results allow the prediction of the parameters involved in ham curing process, demonstrating the viability of the proposed method for the control and monitoring of the different stages until obtaining the final product.