This article introduces a solution approach for the Stochastic Capacitated Vehicle Routing Problem (SCVRP) with uncertain demands, called Robust Simulation-Based (RoSi) approach. RoSi aims at designing route plans that can be more or less robust based on a decision-maker weight, i.e. solutions that resist demand changes with marginal additional (recourse) cost. For that, RoSi combines simulation with heuristics. It transforms a complex SCVRP into a set of deterministic ones, where well-known heuristics can be applied, computing a set of feasible solutions. These solutions are assessed by Monte Carlo simulation, and the one that deals better with demand fluctuation is selected as the final solution. The efficiency of RoSi is compared with those of three methods in the literature: Integer Linear Programming (ILP) model, Stochastic Programming with Recourse (SPR) model, and Robust Bi-Objective (RoBi) approach through numerical experiments. The results show that RoSi outperforms these methods in most scenarios.