Abstract Sand production is a critical problem that causes the industry spending over $3.0 Billion U.S. per year (70% of the wells worldwide have this problem). To mitigate the impact, many operators choose the option of deploying technologies to exclude the sand, and usually reduce the benefits for decrease a risk not quantified. Currently the reservoirs trending to sand production contain an increasing percentage of the world's hydrocarbon reserves. Many of the wells that exploit these resources are producing beyond the limits of their originally estimated useful life, which can result in weak formations. Consequently, it is required being more demanding in the profit margins of the projects of Management and / or sand control achieved at these reservoirs, so it requires a probabilistic risk analysis (PRA) in them, taking into account that the risk and uncertainty are two factors that are often present. This analysis facilitates decision making and allows determine the best Completion and production strategy of the formations sensitive at sand production. Based on the above, this work focuses on developing a methodology for probabilistic risk analysis to evaluate management alternatives and / or exclusion of sand using Monte Carlo simulation. The methodology includes six phases: (1) Selection of alternatives to evaluate and definition of the conditions of production of each one, (2) Structuring the deterministic model of each alternative (3) identification of most impacting variables on the level of production of each alternative and determination of its range of typical behavior (4) Estimation of probability distributions of production for each variable, (5) Monte Carlo simulation for risk assessment of each alternative and selecting the best choice. The methodology was applied to evaluate management alternatives and / or exclusion of sand in the formations sensitive to sand production of the fields: Lisama, Llanito, Galan, Brisas and Yarigui-Cantagallo in Colombia and was compared with the results of the evaluation when using deterministic models. In this paper is present the Application cases in the wells: Lisama 171 and Yarigui 168. Finally, the main findings, conclusions and recommendations obtained in this study are shown.