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Food safety by design: tools and decision support systems  The initial microbial load is crucial for accurately anticipating modelling outcomes. The microbiological investigations can be conducted using either conventional microbiology methods, such as colony counting, or molecular-based approaches, which are generally regarded as more dependable and precise. Both conventional and molecular microbiological analyses have inherent drawbacks. Firstly, they are time-consuming and provide retrospective results. Secondly, they are costly. Thirdly, they often require high-tech molecular tools and highly trained personnel. Lastly, they are typically destructive to test products, which limits their potential for use on-, in-, or at-line.  Exploring methods that can address the aforementioned issues and facilitate the application of models might lead to new opportunities for predicting food rotting and ensuring safety. Food Safety by Design can provide food producers with a data-driven decision support tools which can assist them on decision making processes on potential food safety hazards for their products and production process. Such tools can allow Food Business Operators to (re)design their production process, reduce energy costs and reduce their contribution to the carbon footprint The role of the Unknowns (uncertainty) in decision making and The Unknown Science Serving Predictive modelling in Food Sector.  Uncertainty plays a crucial role in predictive microbiology and risk assessment by acknowledging and quantifying the inherent variability in microbial behaviour and environmental conditions. Predictive models rely on assumptions and data inputs that are subject to fluctuations and unknown factors, making uncertainty an integral aspect of the analysis. Recognizing and quantifying uncertainties helps to establish the reliability of predictions and allows decision-makers to assess the robustness of risk assessments. By incorporating uncertainty into predictive models, researchers and practitioners can provide more realistic and informative estimates, fostering a better understanding of potential outcomes and enhancing the effectiveness of risk management strategies. This approach promotes a comprehensive and transparent evaluation of microbial risks, guiding the development of more resilient and adaptable measures in fields such as food safety, healthcare, and environmental protection.