Abstract: Abstract: In arid Xinjiang of China, a main cotton producing area, irrigation is an important measure of agricultural production, and researches yield rich experimental data. This study aimed to establish a large-scale water-nitrogen coupling model based on comprehensive analysis of existing field experimental data to estimate mulched drip irrigation cotton yield potential in Xinjiang. A total of 172 datasets on Xinjiang from the year of 1998 to 2016 were collected through literature retrieval. They included 19 known cotton varieties with Xinlu as a main variety. Considering data acquisition and climatic conditions, Xinjiang was divided into northern and southern Xinjiang. In each, a water-nitrogen coupling model was established based on random classification of data by different cotton varieties. The model validation showed the model was reliable with determination coefficient (R2) of 0.57, normalized root mean square of error of 11%, and concordance index of 0.85 in the northern region, and R2 of 0.84, normalized root mean square of error of 8.3%, and concordance index of 0.95 in the southern Xinjiang, respectively. Based on the model, the optimal irrigation was 604 and 552 mm in the southern and northern Xinjiang, respectively, and the optimal fertilizer-N application rate was 325 and 354 kg/hm2 in the southern and northern Xinjiang, respectively. Available irrigation amount was 494 mm in 2020 according to Xinjiang 2014—2016 and future planning (2020). Assuming fertilizer-N supply was optimally supplied, based on the established model, the yield potential of the northern and southern Xinjiang was 5 900 and 6 695 kg/hm2 in 2020 under the limits of water sources, respectively. The total lint yield should be about 5.2×106 t in 2020 in Xinjiang. The actual lint yield in 2014 in Xinjiang was about 3.7×106 t, about 71% of the potential under the limits of water resources. The study can provide valuable information for application of mulched drip irrigation and agricultural water resources planning in Xinjiang.