The objective of this study was to assess the performance of Fourier transform infrared (FTIR) spectroscopy as a rapid and non-invasive technique for the automated microbiological quality evaluation of pasteurized vanilla cream, a ready-to-eat milk-based product. Vanilla cream samples were subjected to (i) microbiological analyses for the determination of aerobic plate count (APC), (ii) sensory evaluation, and (iii) FTIR spectroscopy measurements. The analyses were undertaken in cream samples obtained directly from the manufacturer and stored at different isothermal conditions (4, 8, 12, and 15 °C), as well as from retail outlets. Spectral data collected from cream samples were correlated with microbiological and sensory data to discriminate the samples in two quality classes, namely class 1 (accept, APC < 4.5 log CFU/g) and class 2 (reject, APC ≥ 4.5 log CFU/g). Support vector machine classification (SVM-C) models were developed to provide qualitative estimations of the cream samples’ microbiological status based on FTIR spectral fingerprints. The developed SVM models were further validated against independent samples obtained from the market and exhibited a satisfactory performance. Specifically, overall classification accuracies above 90% were obtained for various SVM kernels assayed (linear, polynomial, radial basis function) for the test datasets analyzed, indicating that FTIR spectroscopy could be a promising method for the real-time assessment of vanilla cream’s microbiological quality.