Censored data are seldom taken into account in species sensitivity distribution (SSD) analysis. However, they are found in virtually every dataset and sometimes represent the better part of the data. Stringent recommendations on data quality often entail discarding a lot of these meaningful data, resulting in datasets of reduced size which lack representativeness of any realistic community. However, it is reasonably simple to include censored data in SSD by using an extension of the standard maximum likelihood method. The authors detail this approach based on the use of the R-package fitdistrplus, dedicated to the fit of parametric probability distributions. The authors present the new Web tool MOSAIC_SSD, that can fit an SSD on datasets containing any type of data, censored or not. The MOSAIC_SSD Web tool predicts any hazardous concentration and provides bootstrap confidence intervals on the predictions. Finally, the authors illustrate the added value of including censored data in SSD, taking examples from published data.