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Abstract. The aim of this work was to classify parts of human tooth surface by laser-induced breakdown spectroscopy coupled with multivariate data analysis. The human tooth was irradiated by 110 mJ Nd-YaG laser (1064 nm) under Helium gas with flow rate of 50 ml/s to produce plasma. Photon emission of the plasma was captured by ocean optic spectrometer HR 200 and was displayed a spectra of intensities vs wavelength. The spectra data were analysed by different strategies in principle component analysis (PCA) algorithm for classifying human tooth surface. The spectra data were split into two ranges that were a full window spectra (FW) and special window spectra (SW). Before PCA analysing, the data were treated by different strategies of transformation namely baseline, area normalisation, derivative and original data. The results showed that the special window spectra using baseline transformation could both clustering and distinguishing parts of human tooth surface clearly.