Résumé : Quantile regression allows to assess the impact of some covariate X on a response Y .An important application is the construction of reference curves and conditional predictionintervals for Y . Recently, Charlier et al. (2014a) developed a new nonparametric quantileregression method based on the concept of optimal quantization. This method, as shownin Charlier et al. (2014b), competes very well with its classical nearest-neighbor or kernelcompetitors. In this paper, we describe an R package, called QuantifQuantile, that allowsto perform quantization-based quantile regression. We describe the various functions of thepackage and provide examples.