Abstract: To address the inherent challenges such as difficulties in panelist training, complex operational procedures, and data dispersion associated with Quantitative Descriptive Analysis (QDA), this study explores the applicability, expediency, and reliability of the Pivot-CATA method for the sensory quality assessment of Strong-aroma Baijiu. By integrating the Pivot Profile method with industry expertise, a sensory panel of 41 descriptors was established, characterized by being easy to understand, unambiguous, perceptible, and discriminative. Subsequently, a quantifiable and user-friendly Pivot-CATA methodological framework was developed. Using a 7-point discrete semantic scale, 15 professional panelists evaluated 20 mainstream commercial Strong-aroma Baijiu samples (50%~52 % vol) and subsequently conducted Pivot-CATA sensory evaluation. The experimental data were analyzed using Agglomerative Hierarchical Clustering (AHC) and Correspondence Analysis (CA). The results indicated that AHC classified the 20 samples into high, medium, and low quality grades, revealing discrepancies between quality and price in certain samples. Correspondence analysis (CA) of quality classification and Pivot-CATA further revealed that jiao-aroma, aged-aroma, milky-aroma, various overall aroma perceptions, as well as sourness, sour aftertaste, sweetness aftertaste (Hui gan), astringency, after taste cleanliness and various overall taste feelings were the key discriminative attributes affecting the overall quality and grade of Strong-aroma Baijiu products. Specifically, jiao-aroma, aged-aroma, overall aroma perceptions, sweet aftertaste, aftertaste cleanliness and overall taste feelings enhanced product quality, while milky-aroma, sourness, aftersour and astringent taste had a negative impact. Collectively, these findings establish the Pivot-CATA method as an efficient and accurate tool for characterizing the sensory profiles of Strong-aroma Baijiu, proving suitable for rapid quality differentiation and promoting the industry's exploration of new methodologies. Concurrently, it identifies key sensory attributes essential for quality discrimination, thereby helping consumers better understand Strong-aroma Baijiu quality.