In this chapter, we introduce basic econometric techniques which can be applied to food sciences. We define econometrics and Introduce linear regression models, simple and multiple. We further discuss the Ordinary Least Squares estimation procedure as well as the Gauss-Markov assumptions necessary to ensure the estimators are the most efficient and unbiased in the class of linear estimators. Then, we propose some visual inspection tools to validate the model. The use of categorical variables and interactions is also presented as a way to achieve additional understanding of the relationships among the variables. A brief discussion about inference is also provided in order to give the foundations for hypothesis testing in linear regression models. Some common caveats and violations of assumptions are discussed, such as the issue of multicollinearity and endogeneity and we provide some guidance to approach those problems. Lastly, some practical examples are presented to further illustrate the use of econometric techniques in food science.