Laser induced breakdown spectroscopy (LIBS) technology has the characteristics of speediness, noncontact, no need of sample preparation, which is very suitable for the online analysis of the converter steel composition, because the end-point can be determined by Si and Mn contents and temperature. A qualitative analysis of LIBS is proposed for analyzing the Si and Mn composition in molten steel. Laser excitation spectra are collected by spectrometer, and after the operations of pretreatment and peak searching, with the atomic spectra database (NIST) as the reference standard, the corresponding characteristics of spectral line wavelength and spectral intensity of Si and Mn are found out. Based on the powerful classification function of support vector machine (SVM), 210 sets of 245 sets of data collecting are used to get the support vector classification (SVC) model, which then predicts that 245 groups of data. The accuracy of the model is more than 98%, which can identify the corresponding wavelength of Si and Mn very well, and can be used under the condition of the same experimental conditions with significant reduction to the LIBS qualitative analysis time.