High mortality rates associated with oral cancers can be primarily attributed to failure of current histological procedures in predicting recurrence. Identifying recurrence related factors can lead to improved prognosis, optimized treatment and enhanced overall outcomes. Serum Raman spectroscopy has previously shown potential in diagnosis of cancers like head and neck, cervix, breast, oral cancers and also in predicting treatment response. In the present study, serum was collected from 22 oral cancer subjects [with recurrence (n=10) and no–recurrence (n=12)] before and after surgery and spectra were acquired using Raman microprobe coupled with a 40X objective. Spectral acquisition parameters were: λex = 785 nm, laser power = 30 mW, integration time: 12 s and averages: 3. Data was analyzed in patient-wise approach using unsupervised PCA and supervised PC-LDA, followed by LOOCV. PCA and PC-LDA findings suggest that recurrent and non-recurrent cases cannot be classified in before surgery serum samples. An average classification efficiency of ~ 78% among recurrent and non-recurrent subjects in after-surgery samples was obtained. Thus, RS of post surgery serum samples may have the potential to predict probability of recurrence.