Industrial expansion in Zambia has increased pollutant loads discharged into watercourses, necessitating robust and efficient effluent treatment. Existing systems often operate sub-optimally, with limited comprehensive analysis integrating technical performance with environmental and economic factors. This study aimed to assess the operational efficacy of prevalent industrial effluent treatment systems and develop a framework for their techno-environmental optimisation to enhance pollution control. A mixed-methods approach was employed, involving field sampling and laboratory analysis of influent and effluent from selected treatment plants. Performance was evaluated against Zambian regulatory standards. A techno-environmental optimisation model was developed using linear programming, with the objective function $\min Z = \sum_{i=1}^{n} (C_i x_i + E_i y_i)$ subject to contaminant removal constraints, where $C_i$ and $E_i$ represent cost and environmental impact coefficients for technology $i$. Approximately 65% of assessed systems failed to consistently meet permissible discharge limits for key parameters, notably biochemical oxygen demand and heavy metals. The optimisation model, validated with field data, demonstrated a potential reduction in operational costs by up to 22% while improving compliance, with a 95% confidence interval for the cost-saving estimate of [18%, 26%]. Current treatment infrastructure requires significant operational improvements. The proposed optimisation framework provides a viable, evidence-based pathway to enhance system performance and regulatory compliance cost-effectively. Implement regular performance audits guided by the developed model. Policy should encourage adoption of integrated techno-environmental assessments for new system designs and retrofits. effluent treatment, optimisation model, water pollution, industrial wastewater, Zambia, linear programming This research provides a novel, integrated techno-environmental optimisation model, calibrated with primary field data, to guide the cost-effective upgrade of industrial wastewater management.