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The development of grass-feeding livestock breeding is the key to promoting the transition from grain-consumption type animal husbandry to grain-saving type animal husbandry in China, and to solving the problem of competition for grain between people and livestock. From the perspective of economic geography, this paper first defines the conversion standard for the breeding quantity of livestock, and then uses exploratory spatial data analysis technology and econometric models and methods to systematically investigate the sequential variation process, geographical aggregation characteristics, and influencing factors of grass-feeding livestock breeding in China. The study results show the following: 1) The breeding quantity of grass-feeding livestock in China has an obvious overall growth trend, but there is an obvious difference among the livestock species. During the period 1978–2012, the breeding quantity of grass-feeding livestock in China grew by 92.5%; and the breeding quantity within the same period was beef cattle > sheep > dairy cow. 2) On the county scale, the number of increasing areas of the breeding quantity of grass-feeding livestock is larger than the number of decreasing areas, and the growth rate of breeding quantity of grass-feeding livestock in northern China is higher than that in southern China, which initially forms the pattern of "hot in the north and cold in the south". 3) The spatial Durbin model shows that the per capita output of grain, proportion of productive land area, urban per capita disposable income, agricultural mechanization level, agricultural labor productivity and policy factor have positive effects on the development of grass-feeding livestock breeding, while the per capita GDP, urbanization level and proportion of non-agricultural income have obvious negative effects on it. 4) Grass-feeding livestock breeding in China can be divided into six major types of areas, and each type of area should be regulated and controlled in terms of their respective focus of attention according to regional conditions and situation of agricultural production.