To address the monitoring problem in high-intensity focused ultrasound (HIFU) therapy, a new method is proposed for identification of tissue damage without the need for additional monitoring sources. The method involves studying the multiscale fuzzy entropy (MFE) of the fundamental and second harmonic of the HIFU echo. The HIFU echo signal is denoised using spectral subtraction, and then the fundamental and second harmonic components of the signal are extracted using the kullbackleibler divergence-optimized variational mode decomposition (KLD-VMD) method. Finally, the MFE combining the fundamental and second harmonic is used to identify tissue damage. The validity of the method is verified using the equal error rate (EER), where a lower EER indicates better recognition. The study also compares the KLD-VMD method with other decomposition methods such as VMD, EMD, and ITD, in combination with MFE for tissue damage identification. The experimental results demonstrate that the tissue damage identification based on KLD-VMD and MFE achieves an EER of 5.1%, which is better compared to the other methods. Furthermore, the results also show that combining the fundamental and second harmonics improves the identification performance compared to using either echo alone. This study provides a new monitoring method for HIFU therapy with potential practical applications.