One of the challenges in deciding on industrial cleaner production implementations is the selection of the proper technique. This study presents a new approach to the selection of energy efficiency (EE) techniques employing the “Technique for Order of Preference by Similarity to Ideal Solution” (TOPSIS) model. Although the TOPSIS model has been used for various decision-making processes in some other sectors, it was not specifically used for the prioritization of EE techniques before. This model was applied for the first time in an integrated home textile enterprise. Initially, a wide list of best available techniques (BATs) and other measures were prepared to achieve electricity and thermal EE in the enterprise. TOPSIS analysis results indicated that out of this wide list, only seven of the techniques should be further investigated. These techniques can be listed as monitoring fabric moisture and optimizing passage speed in the stenters, control of recirculated air in stenters, process optimization in finishing processes, modification of the humidification-ventilation system, optimization of indoor lighting, establishing an energy monitoring system, insulation of pipe, valves, and tanks. Reductions in air emissions, and energy consumptions (electricity, steam natural gas) were calculated based on each EE technique. Ultimately, following potential reductions were calculated: 2.2–3.5% in electricity, 0.5–1.5% in steam, 6.3–13.5% in natural gas, and 8-16.5% in air emissions. Potential payback periods of the priority EE techniques were calculated as less than 40 months. TOPSIS model provided an effective roadmap in the selection of EE techniques and by this model, industries may save time and effort during decision-making for cleaner production investments. Furthermore, the TOPSIS model will also help the decision of optimum techniques to be implemented in the enterprise, providing economical savings and environmental performance improvement.