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This study proposes a formula for prediction of maturity index (I_m) using physico-chemical characteristics and overall acceptability (OA) of a sensory panel for mangoes from orchards of nine Indian states. Computed I_m values were found to be in agreement with both OA scores and the perceptions of experienced farmers. NIR spectra of 1180 mangoes were acquired. Multiple-linear regression (MLR) and partial least square (PLS) models were developed in the wavelength range of 1200–2200 nm to predict I_m. The best prediction was achieved using PLS model after MSC data treatment in the wavelength range of 1600–1800 nm. Multiple correlation coefficients (R) for calibration and validation of PLS model were 0.74 and 0.68, respectively. Lower difference in standard errors of calibration (0.305) and prediction (0.335), indicated the potential of NIRS in prediction of the maturity non-destructive.