Experimental batches of chilled boneless slices of pork meat have been stored aerobically in sterile Petri dishes and total aerobic plate counts (TAPC) and sensorial observations were made periodically during storage to monitor bacterial growth and apparent deteriorative changes at 4, 8 and 12 °C, respectively. Near infrared spectroscopy (diffuse reflectance) measurement was performed on replicate meat samples in the wavelength range of 1000–1800 nm. Second derivative and multiplicative scatter correction were performed on the spectra as data pre-treatments. Principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for observation of discrimination of the samples due to loss of freshness and onset of bacterial spoilage as a function of the storage time. The percentage of correctly classified samples decreased somewhat by increasing the storage temperature. Partial least squares (PLS) chemometric model was developed to predict and quantify bacterial loads from the scatter corrected 2nd derivative spectra. PLS evaluation (predicted versus measured TAPC values) — when bacterial counts at all sampling days and storage temperatures were taken into account — resulted in a correlation coefficient of 0.977, and a root mean square error of prediction (RMSEP) 0.438 log colony forming units/g. These preliminary results indicate the potential of utilising near infrared diffuse reflectance spectroscopy in combination with multivariate statistical methods to monitor loss of freshness and detect bacterial spoilage of meat samples rapidly before deleterious microbial changes become apparent. However, much larger number of samples should be studied to ascertain properly the prediction power of the spectroscopic method.