Model-based contaminant source identification plays an important role in effective site remediation. In this article, a contaminant source identification toolbox (CONSID) is introduced as a framework for solving contaminant source identification problems. It is known that the presence of various types of model uncertainties can severely undermine the performance of many existing source estimators. The current version of CONSID consists of two robust estimators for recovering source release histories under model uncertainty; one was developed in the deterministic framework and the other in the stochastic framework. To use the robust estimators provided in CONSID, the user is required to have only modest prior knowledge about the model uncertainty and be able to estimate the bound of model deviations resulting from the uncertainty. The toolbox is designed so that other source estimators can be added easily. A step-by-step guidance for using CONSID is described and an example is provided.