Cocoa powder is a global product of great value that can be adulterated with low-cost raw materials such as carob flour without changing the characteristics of color, aroma and flavor of the product. The use of rapid methods, as a NIR technology combined with multivariate analysis, is of interest for this detection. In this work, 216 adulterated samples prepared by blending commercial cocoa powders with different alkalization levels (n = 12) with commercial carob flour (n = 6) in different proportions (0-60% of adulteration) were analyzed. The diffuse reflectance spectra of the samples were acquired from 1100 to 2500 nm using a Foss NIR spectrophotometer. A qualitative and quantitative analysis was done. For the qualitative analysis, a principal component analysis (PCA) and a partial least squares discriminant analysis (PLS-DA) was performed. The coefficient of determination (R2) of the model PLS-DA was 0.969 and the coefficient of determination of the validation (R2CV), based on a full cross validation was 0.901 indicating good calibration with good predictability. These results indicate that it is possible to distinguish between pure cocoa powders from the adulterated samples. For the quantitative analysis a partial least squares (PLS) regression analysis was performed. The most robust model of PLS prediction was obtained with 1 factors (LV) at coefficient of determination (R2) of 0.980 and a root mean square error of prediction (RMSEp) of 3.237 % for the external validation set. These data lead to the conclusion that NIR technology combined with multivariate analysis allows the identification and determination of the amount of natural cocoa powder present in a mixture adulterated with carob flour.