To improve the accuracy of quantitative analysis of laser-induced breakdown spectroscopy (LIBS), the quantitative analysis of Mn in different alloy steels is conducted by LIBS. The calibration model is established by combining support vector regression (SVR) to study the influences of different input vectors in the SVR model, and the internal standard method is used to correct the results. The results show that when the input vectors are the internal standard element correction and signal-to-back ratio, the relative standard deviation and the relative error of the test set are 2.6% and 11.97%, respectively, and the regression effect is optimal. In the quantitative analysis of Mn in the alloy steel, the corrected binary input vector reduces the parameter fluctuation, corrects the matrix effect, and provides a reference for the optimization of the input data for the quantitative analysis of steel elements by LIBS.