The invention discloses a self-adapting peak search method for a spectrum of a semiconductor laser. The self-adapting peak search method comprises the following steps of: establishing a local maximum matrix of a spectrum data sequence, correcting the matrix with a row vector feature, positioning a peak value according to a column vector feature of the corrected matrix, and performing further correction and compensation with a certain method. The method has relatively good noise resistance, and the whole search process is free of human intervention, so that the adaptivity and the robustness are high and real-time calculation requirements are met. An actually measured data calculation result shows that compared to a direct comparison method, an optimized derivative method and a genetic algorithm, the self-adapting peak search method has the characteristics that the advantages in check accuracy and calculation time are obvious, the average check accuracy can reach 98%, the average calculation time is only 0.12 seconds, and the self-adapting peak search method can be applied to real-time analysis of actually measured spectrums of semiconductor lasers.