This study investigates the development and performance of geopolymer bricks using polyethylene terephthalate (PET) waste and various industrial by-products (rice husk ash, ground granulated blast furnace slag, red mud, and construction and demolition waste). The research aims to explore the potential of these materials as sustainable building materials, aligning with the principles of the Circular Economy. Key findings include a 14.75% decrease in workability and a 75% reduction in compressive strength when PET waste replaces sand filler up to 100%. Dry density decreases, and water absorption increases to 13.73% with full sand replacement. Impact resistance improves by 57% with plastic waste inclusion, enhancing ductility and thermal conductivity. Microstructural analyses reveal correlations between physical-mechanical properties and changes in porosity, microcracks, and bond strength. Machine learning, particularly linear regression, effectively predicts strength parameters with an efficacy of up to 100% and an R-square of 0.998. The study concludes that these geopolymer bricks offer a substantial environmentally friendly solution for the building and construction industry, contributing to sustainable practices and environmental sustainability.This study investigates the development and performance of geopolymer bricks using polyethylene terephthalate (PET) waste and various industrial by-products (rice husk ash, ground granulated blast furnace slag, red mud, and construction and demolition waste). The research aims to explore the potential of these materials as sustainable building materials, aligning with the principles of the Circular Economy. Key findings include a 14.75% decrease in workability and a 75% reduction in compressive strength when PET waste replaces sand filler up to 100%. Dry density decreases, and water absorption increases to 13.73% with full sand replacement. Impact resistance improves by 57% with plastic waste inclusion, enhancing ductility and thermal conductivity. Microstructural analyses reveal correlations between physical-mechanical properties and changes in porosity, microcracks, and bond strength. Machine learning, particularly linear regression, effectively predicts strength parameters with an efficacy of up to 100% and an R-square of 0.998. The study concludes that these geopolymer bricks offer a substantial environmentally friendly solution for the building and construction industry, contributing to sustainable practices and environmental sustainability.