This paper presents a feasible methodology to quantify and classify the mafurra methyl biodiesel content in a diesel blend using Fourier transform mid-infrared spectroscopy (FT-MIR) in combination with partial least squares (PLS) and partial least squares discriminant analysis (PLS-DA) and variable selection (siPLS and siPLS-DA). When the spectra were divided into 30 equally spaced intervals, the models combining four intervals (that is, si(4)PLS(30) and si(4)PLS-DA(30)) showed statistically better results than PLS and overall PLS-DA. This compatikin was performed on the basis of the application of F test values. The si(4)PLS(30) model was validated on the basis of several figures of merit, and strong correlations between the actual concentration and forecasted values Of the calibration and prediction sets, with a correlation coefficient higher than 0:99, were observed. The efficiency of the si(4)PLS-DA(30) model was evaluated on the basis of sensitivity and specificity, and these parameters showed values of 1, indicating 100% correct classification of the calibrated and forecasted 137 and BX samples. The analytical method developed in this research is feasible and efficient and can be used by supervisory bodies for the quantitative and qualitative control of fuels because it is of relatively low cost and enables rapid, direct, and in situ analysis using portable equipment.