In a closed loop structure, the circular economy reflects a concept for converting material and energy wastes into capital for other purposes. The circular economy's key goal is to reduce energy and material waste. The best-case scenario will be to eliminate wastes and repurpose them, which is one of the key goals of the circular economy. The circular economy and sustainable development are inextricably linked. The framework reflects resource reuse and recycling in order to reduce waste and the use of biodegradable items that can be returned to the ecosystem after rejection. Many programs are being developed to incorporate the circular economy in order to apply the system's best practices. Recycling and reusing goods for the same or new items are the best practices for reducing waste and energy consumption. The main goal of the study was to analyze the effect of waste generation and recycling on production-based CO2 intensity based on circular economy concept. For such a purpose adaptive neuro fuzzy inference system (ANFIS) was implemented since the methodology is suitable for statistical investigation of strongly nonlinear data sample due to features of fuzzy logic system. Generated and recycled waste including biomass is the most influential factors for the production-based CO2 intensity based on circular economy concept. The obtained results could represent the best practices for implementation of circular economy concept.