Meta-analysis enables to re-analyse “existing” data, generated previously by scientists working on a comparable subject. These existing data are made available through peer-reviewed publications but also through scientific reports from regulatory agencies, database, etc. Since the data have been collected by different research teams, in different laboratories with different experimental set up (within the same subject of interest, though), there is a natural heterogeneity between studies. For instance when studying the effect of heat treatment on survival of bacteria, several research teams could have worked on the same bacterial species and the same temperature range, but not exactly with the same experimental protocols. The choice of strains and heat-treatment medium could also differ. The advantage of the meta-analysis is to take explicitly the heterogeneity due to the study and other co-variables (e.g. strain, media) into account; the inter-study variation is quantified. As a consequence, meta-analysis enables to produce a more precise estimate of the effect of a particular treatment (e.g. heat-treatment effect) than a statistical analysis where the data are pooled regardless their sources. Meta-analysis is widely used in medical research; it is gaining interest in food safety and risk assessment. It has been used from estimating the prevalence of hazards on raw materials up to dose-response characterization. It has been also widely used to re-analyse existing data collected on either survival or growth of microorganisms in food matrix. That makes a lot of sense considering the abundant literature on microbial survival studies (since mid of the 20th century) and on microbial growth (with the boom of challenge testing and predictive modelling in the last 30 years). Meta-analysis could be equally valuable in food safety and food spoilage applications. In this presentation, meta-analysis principle and added value in food microbiology will be illustrated though various concrete examples.