Open AccessDemand forecasting plays an increasingly relevant role within competitive and globalized marketplaces, in as much as operations planning and subsequent transition into a sustainable chain of supplies, is concerned. To this effect, the purpose of this study is to present the application of demand forecasting as a strategic sustainability tool at a Brazilian SME. Therefore, this is a descriptive, ex-post facto and cross-cut, sectional time case study, which employs qualitative and historical quantitative and direct observational data and that utilizes, as both indicators of the level of service offered to consumers and of opportunity costs the artificial neural networks model and fill-rates, for demand forecasting and response purposes. The study further established cause-effect relationships between prediction accuracy, demand responsiveness and process-resulting economic, environmental and social performances. Findings additionally concurred with both widely acknowledged sustainability concepts - NRBV (Natural-Resource-Based View) and 3BL (Triple Bottom Line) - by demonstrating that demand forecasts ensure the efficient use of resources, improvements in customer responsiveness and also mitigate supply chain stock out and overstock losses. Further to the mentioned economic benefit, demand forecasting additionally reduced the amount of waste that arises from retail product shelf-life expiration, improving the addressing of demand itself and of customer satisfaction, thus driving consequent environmental and social gains.