The growing demand for whey protein supplements has made them the target of adulteration with cheap substances. Therefore, Raman spectroscopy in tandem with chemometrics was proposed to simultaneously detect and quantify three common adulterants (creatine, l-glutamine and taurine) in whey protein concentrate (WPC) powder. Soft independent modeling class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA) models were built based on two spectral regions (400–1800 cm−1 and 500–1100 cm−1) to classify different types of adulterated samples. The most effective was the SIMCA model in 500–1100 cm−1 with an accuracy of 96.9% and an error rate of 5%. Partial least squares regression (PLSR) models for each adulterant were developed using two different Raman spectral ranges (400–1800 cm−1 and selected specific region) and data pretreatment methods. The determination coefficients (R2) of all models were higher than 0.96. PLSR models based on typical Raman regions (500–1100 cm−1 for creatine and taurine, the combination of range 800–1000 cm−1 and 1300–1500 cm−1 for glutamine) were superior to models in the full spectrum. The lowest root mean squared error of prediction (RMSEP) was 0.21%, 0.33%, 0.42% for creatine, taurine and glutamine, and the corresponding limit of detection (LOD) values for them were 0.53%, 0.71% and 1.13%, respectively. This proves that Raman spectroscopy with the help of multivariate approaches is a powerful method to detect adulterants in WPC.