With the fast progress in multi-channel detection technology, integrated microscopy and data acquisition and analysis methods, the technology of infrared and Raman spectroscopy were intensively and extensively applied in biological and biomedical fields. In this work, Raman microspectroscopy and imaging was applied to examine human hair samples which were retrieved from both healthy persons and cancer patients. Through MATLAB programming, multivariate statistical analysis methods such as principal component analysis (PCA), hierarchical clustering analysis (HCA) were used to analyze the hair’s spectral data. The results revealed the notable difference in hair spectral analysis between the healthy people and the cancer patients, indicating that the technique of Raman microspectroscopy and imaging combined with the proper data treatment approach have a promising potential for the clinical application in disease diagnosis and prediction.