This study aimed to evaluate the utilisation of near-infrared (NIR) spectroscopy combined with chemometric techniques to identify the addition of goat liver to goat minced meat and to monitor the shelf life of the samples up to 8 days of storage. Mix samples were created by adding goat liver to goat meat in different ratios (0%, 2%, 4%, 6%, and 8% w/w), and after mincing, the samples were stored under chilled (2-4 degrees C) conditions for 8 days. The NIR spectra, CIELab parameters, and pH of the mixture samples were collected at the start of the study and after 2, 4, 6, and 8 days of storage. The mince became darker with the increase in days of storage, while the pH value was not affected by days of storage. Partial least squares (PLS) regression was used to develop calibration models for the CIELab parameters to predict the level of liver addition to minced meat and to predict days of storage. The standard error in cross-validation (SECV) and the coefficient of determination in cross-validation (R2cv) were 0.10 (SECV: 3.3), 0.63 (SECV: 1.5), and 0.60 (SECV: 0.90) for L*, a*, and b*, respectively. The R2CV and SECV were 0.32 (SECV: 2.4%) and 0.92 (SECV: 0.98 days) to predict the level of liver addition to minced meat and days of storage, respectively. The NIR calibration models developed to predict the CIELab parameters and level of addition of liver to minced meat were inadequate for predicting new samples. On the other hand, the PLS models developed could predict the days of storage, R2cv 0.92 (SECV: 0.98 days). Compared with traditional methods such as CIELab or pH measurements, NIR spectroscopy can yield results more rapidly. However, the variability in the data set should be increased to allow the development of more reliable models.