Probabilistic approaches to hazard assessment use species sensitivity distributions (SSDs) to characterize hazard for toxicants exposure for different species within a community. Many of the assumptions at the core of SSDs are unrealistic, among them the assumption that the tolerance levels of all species in a specific ecological community are a priori exchangeable for each new toxic substance. Here we propose the use of a particular test to detect situations where such an assumption is violated. Then, a new method based on non‐nested random effects model is required to identify novel SSDs capable of taking into account species non‐exchangeability. Credible intervals, representing SSD uncertainty, could be determined based on our procedure. This leads to new and reliable estimates of the environmental hazard. We present a Bayesian modeling approach to address model inference issues, using Markov chain Monte Carlo sampling.