To support systematic carbon-reduction decision-making in integrated steelworks, this study develops a bottom-up framework that combines process-based mechanisms with data-driven regression for the blast furnace–basic oxygen furnace (BF–BOF) route. The framework links material, energy, exergy, carbon, and economic value flows and formulates a multi-objective optimization problem that minimizes exergy intensity and CO₂ emission intensity while maximizing the cost–benefit ratio (CBR) per tonne of steel product. For the representative 380CL product, the selected optimized solution reduces CO₂ emissions from 2.082 to 1.929 t CO₂/t-SP (7.35%) and exergy consumption from 19.175 to 18.027 GJ/t-SP (5.99%) while increasing the CBR from 0.732 to 0.771 (5.33%). One-factor-at-a-time sensitivity analysis shows that material blending, moisture content, coke and scrap ratios, blast conditions, and interface temperatures can have different environmental and economic effects under the assumed plant conditions. The methodological contribution is the product-level coupling of exergy, carbon, and economic value flows in a bottom-up BF–BOF model, rather than the individual identification of already-known process effects. The quantitative results are specific to the case enterprise, product, equipment configuration, material qualities, energy and carbon prices, and operating constraints. The framework should not be directly transferred to electric-arc-furnace (EAF) steelmaking without route-specific reformulation; validation across additional plants and products is needed.