In order to improve the correct classification rate of analog circuit fault diagnosis and recognition, a simulation circuit fault diagnosis method based on lifting wavelet transform and chaotic firefly algorithm (CFA) is proposed to optimize LSSVM parameters. Firstly, the wavelet transform is applied to the output voltage signal of the measured circuit. Then, the transformed data is analyzed by factor analysis method, and the optimized data is taken as the fault feature set of different modes. Finally, the obtained fault feature set as sample is imported into the CFALSSVM model for troubleshooting. The experimental results show that the fault diagnosis accuracy of this method is more than 98%, which improves the diagnostic performance and can be applied to the fault diagnosis of analog circuits.