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This paper presents a general method for measuring plant-wide industrial energy savings and demonstrates the method using a case study from an actual industrial energy assessment. The method uses regression models to characterize baseline energy use. It takes into account changes in weather and production, and can use sub-metered data or whole plant utility billing data. In addition to calculating overall savings, the method is also able to disaggregate savings into components, which provides additional insight into the effectiveness of the individual savings measures. Although the method incorporates search techniques and multi-variable least-squares regression, it is easily implemented using data analysis software. The case study compared expected, unadjusted and weather-adjusted savings from six recommendations to reduce fuel use. The study demonstrates the importance of adjusting for weather variation between the pre- and post-retrofit periods.