Currently, the first problem that has gradually emerged from the development of modern industries is how to achieve ecological civilisation. With the ambitious goals of China’s “Dual Carbon”, we need to know how financial performance in enterprises relates to green development. Based on the data from 2018 to 2022, this paper will examine the relationship between the financial health, scale, and extent of environmental pollution of industrial enterprises in China. A reproducible Python/KNIME pipeline has been employed to process the data and train a model. Exploratory Data Analysis shows that the distribution of wastewater discharge intensity is right-skewed, and a small number of enterprises are responsible for a large amount of pollution. Based on the empirical model, there are several reasons for the irregular distribution of industrial pollution. The small R-squared of OLS is about 0.02, and Random Forest has reduced the average baseline error (MAE 1.25) by 74%. To avoid circular reasoning, K-means clustering was applied only to the financial and scale attributes, and the Silhouette score was also obtained. Post-hoc environmental analysis of the three derived financial clusters (Large-Scale Heavyweights, Mid-Sized Manufacturers and Low-Impact Micro-Enterprises) showed different structural emission patterns. Therefore, various environmental regulations and specific green finance will be implemented.