This work presents an application of an integrated model for the evaluation and probabilistic optimization of projects portfolios, integrating economic, risk and social and environmental impacts analysis. The model uses the Monte Carlo simulation and linear programming techniques for treatment of uncertainties and optimization of projects portfolio. The integrated model was applied in a Brazilian company of electricity distributions. The portfolio of selected projects was related to the expansion of the supply of electricity in a town in the south of the country and the analysis horizon was set in ten years. The aim of the application was to maximize the return for the implementation of a substation and a transmission line in a set of projects, which are diverse in terms of costs, benefits and environmental and social impacts. As a result, the model generates: i) an analysis of each individual projects, from budget information (costs and benefits involved) and estimation of social and environmental impacts generated by the project and the risks (uncertainties) involved and ii) the optimum combination of projects that the company should prioritize to ensure the best financial return and lower social and environmental impacts, thus generating an optimal portfolio.This work presents an application of an integrated model for the evaluation and probabilistic optimization of projects portfolios, integrating economic, risk and social and environmental impacts analysis. The model uses the Monte Carlo simulation and linear programming techniques for treatment of uncertainties and optimization of projects portfolio. The integrated model was applied in a Brazilian company of electricity distributions. The portfolio of selected projects was related to the expansion of the supply of electricity in a town in the south of the country and the analysis horizon was set in ten years. The aim of the application was to maximize the return for the implementation of a substation and a transmission line in a set of projects, which are diverse in terms of costs, benefits and environmental and social impacts. As a result, the model generates: i) an analysis of each individual projects, from budget information (costs and benefits involved) and estimation of social and environmental impacts generated by the project and the risks (uncertainties) involved and ii) the optimum combination of projects that the company should prioritize to ensure the best financial return and lower social and environmental impacts, thus generating an optimal portfolio.