Abstract: By integrating local resource endowments to develop leading industries with comparative advantages, and enhancing agricultural competitiveness through industrial integration, technological empowerment, and other approaches, agricultural industry-strong towns have promoted the circulation of resource elements among towns and accelerated the process of agricultural and rural modernization. To clarify the spatial distribution characteristics of different categories of national-level agricultural industry-strong towns and their influencing factors from 2018 to 2024, these towns are classified into 9 categories based on the leading industrial categories they declared. A combination of spatial analysis methods, including the average nearest neighbor index, kernel density estimation, and geographical detector, was comprehensively adopted to explore the spatial pattern and driving factors, so as to provide data support for promoting industrial development and advancing the construction of industry-strong towns. The results show that: (1) A total of 1,709 agricultural industry-strong towns have been approved nationwide, most of which are distributed in the third topographic step and along water sources. The results show that the spatial distribution is uneven overall, exhibiting a “northeast–southwest” pattern. Kernel density analysis reveals that towns specializing in different product categories exhibit the distribution characteristics of "category-region matching and core-led radiation". Among them, grain and oil industry-strong towns are the largest in number, reaching 389, while edible fungus industry-strong towns are the smallest, with only 60. Overall, three major high-density clusters have been formed in the border areas of Hebei-Shandong-Henan, Jiangsu-Zhejiang, and Sichuan-Chongqing.(2) At the provincial level, the traditional major agricultural provinces—Shandong, Sichuan, and Henan—still have a relatively large number of such towns, and the development of agricultural industry-strong towns in these provinces is relatively sound both in quantity and spatial layout. Based on the calculation of the average nearest neighbor index and distribution density, 17 provinces show dense distribution characteristics. Specifically, six regions (Shandong, Henan, Guangdong, Jiangsu, Hubei, and Chongqing) belong to the dense agglomeration type; Beijing, Tianjin, and Shanghai belong to the dense uniformity type; and three autonomous regions (Xinjiang, Inner Mongolia, and Tibet) present the scattered agglomeration type.(3) Analysis via the geographical detector shows that the agricultural production scale and regional economic development level have significant single-factor explanatory power for the distribution of industry-strong towns. Among them, the total output value of agriculture, forestry, animal husbandry, and fishery has the strongest explanatory effect, playing an important role in improving agricultural development level and optimizing industrial structure. In contrast, regional and policy factors have weak independent explanatory effects, but show stronger explanatory power through interactions with other factors. In conclusion, the future development of agricultural industry-strong towns should determine product category positioning based on local resource endowments, adhere to the principles of adapting to local conditions and differentiated development, and give full play to comparative advantages. Through scientific planning and rational layout, we should promote clustered development to improve factor efficiency, and steadily advance agricultural industry-strong towns toward a path of differentiated, intensive, and high-quality development.