A novel approach called equal probability sampling (EPS) is used for analyzing uncertainty and sensitivity in thermodynamic models. Uncertainty and sensitivity analysis for simulation and design of industrial processes are becoming increasingly important. The (EPS) method produces more realistic results in uncertainty analysis than methods based on other sampling techniques such as Latin hypercube sampling (LHS) or shifted Hammersley sampling (SHS), when parameters are highly correlated. When parameters are not correlated, EPS reduces to the LHS method. The EPS method is based on resampling to obtain uniform coverage over level sets of the objective function used to obtain the parameters of the model. The existence of unfeasible situations is substantially reduced with EPS. It can be extended to any regression model describing other kinds of physical applications and can be used as a better tool to estimate more reliable safety factors in the design and simulation of industrial chemical processes.