Since the closure of mining activities in 2003, the coal basin of Gardanne in South-East France has experienced thousands of small-magnitude earthquake events, mostly triggered by the flooding of mine workings. Some of these events have been powerful enough to be strongly felt by the population, generating nuisance and concern about potential damage to buildings. The aim of this study is to improve the characterisation of the level of ground motion at the surface, by developing a ground-motion model for post-mining induced seismicity, based on several years of recorded data. A Bayesian-based method is applied to the data in order to account for uncertainties in the estimation of moment magnitude. Station-to-station ground-motion site terms are also quantified for the nine recording stations in the area, thus providing additional information on the local site conditions. The developed model is compared to existing prediction equations for seismicity induced by other types of anthropic activities, confirming the need for a specific model in the case of post-mining induced seismicity. Finally, the Gardanne ground-motion model is also integrated with a shake-map procedure, showing how this predictive model may be merged with recorded data in order to generate rapid estimates of shaking levels in the area.