Shelf-life validation is a critical aspect in ensuring food safety and quality as well as compliance with legal and commercial standards. The food industry has taken different approaches to determine product shelf life, such as considering existing data sources, laboratory experiments, or inoculation studies and more recently, by predictive models, that have several advantages with respect to more traditional methods (e.g., cost-effective and rapid response). In this chapter, an innovative protocol is presented, with an aim to guide end users in the selection, application, and performance assessment of predictive microbiology models for shelf-life validation, using an example with Listeria monocytogenes in a cured-raw meat product. This work provides a bullet-based scheme, defining the main aspects and steps needed to develop an effective model deployment, encompassing, among others, scope definition, model searching, available predictive tools, model selection supported by a tailor-made decision tree, and the final application by using the predictive toolbox, MicroHibro ( www.microhibro.com ).