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We propose a Java library, called robustDEA, facilitating the exploration of all scenarios pertinent to Data Envelopment Analysis. These scenarios encompass feasible weights for inputs and outputs, other model parameter values, and the performances of units under examination. The software conducts robustness analysis employing either ratio-based or additive value efficiency models. The integrated methods employ mathematical programming to deliver precise, robust outcomes and Monte Carlo simulations for generating stochastic acceptability indices. The software considers various dimensions of efficiency – scores, pairwise relations, and rankings – while accommodating user-defined preferences through linear constraints and the hierarchical structure of indicators. It has been applied to real-world problems across economics, energy, healthcare, and transport.