The traditional Chinese medicine (TCM) extraction process is a complicated dynamic system with many variables and disturbance. Therefore, multi critical quality attributes (CQAs) monitoring is of great significance to understand the whole process. Spectroscopy is a powerful process analytical tool used for process understanding. However, single senor sometimes could not provide comprehensive information. Sensor fusion is a very practical method to overcome this deficiency. In this study, the extraction process of Xiao’er Xiaoji Zhike Oral Liquid (XXZOL) was carried out in pilot scale, where near infrared (NIR) spectroscopy and mid infrared (MIR) spectroscopy were collected to determine the concentrations of seven CQAs (synephrine, arecoline, chlorogenic acid, forsythoside A, naringin, hesperidin and neohesperidin) during extraction process. Based on fused data blocks, fusion partial least squares (PLS) models were established. Two fusion data blocks are obtained from the concatenation of original spectra (low-level data fusion) and the concatenation of characteristic variables based on band selection (mid-level data fusion) respectively. The results indicated that for all seven analytes, the mid-level data fusion models were superior to the single spectral models, with the prediction performance significantly improved. Specifically, the coefficients of determination (Rp2 and Rt2) of NIR, MIR and fusion quantitative models were all higher than 0.95. The relative standard errors of prediction (RSEP) values were all within 10%, except for models of neohesperidin, which were 10.76%, 12.39%, 12.05%, 10.03% for NIR, MIR, low-level and mid-level models respectively. These results demonstrate that it is feasible to monitor the extraction process of Xiao’er Xiaoji Zhike Oral Liquid more accurately and rapidly by fusing NIR and MIR spectroscopy, and the proposed approach also has vital and valuable reference value for the rapid monitoring of the mixed decoction process of other TCM.