Green development is key to promoting regional sustainable development. We construct an evaluation index system for green development levels based on the “sansheng” dimensions—production, living, and ecology. We rely on the “sansheng” (production, living, and ecology) dimensions, combined with the analytic hierarchy process (AHP) and the entropy weight method to analyze indicator weights, to construct an evaluation index system for green development levels. This system enables the identification of the evolution patterns of green development and the analysis of driving factors in the Chengdu-Chongqing economic zone from the “sansheng” perspective. The results indicate that: (1) The green development level in the Chengdu-Chongqing Economic Zone has been continuously rising, with the average index increasing from 0.197 to 0.254. Yuzhong District and Chengdu City have shown particularly high green development levels; in 2020, the green development level index for Yuzhong District reached 0.568, while Chengdu City’s index reached 0.522. (2) The spatial clustering of green development levels in the Chengdu-Chongqing economic zone exhibited a trend of first strengthening and then weakening, with the highest clustering degree observed in 2015. (3) National strategies have significantly promoted the improvement of regional green development levels. The average green development index during the pre-establishment, initial development, and rapid development stages of the Chengdu-Chongqing Economic Zone increased from 0.205 to 0.229, and then to 0.254. (4) The Theil index results show an increase in the disparity of green development levels among different regions within the Chengdu-Chongqing Economic Zone.The results of the optimal scaling regression model show that the driving factors with a significant impact on the level of green development include the Number of physicians per million people, Public library book collections Per 100 people, Per capita regional GDP, and Number of secondary schools Per million people, each contributing over 15% to the impact. These findings provide valuable data support for formulating regional economic development strategies and are conducive to advancing sustainable development.