In recent years, as detailed in several monographs, derivations of the fractional differential equations and fractional integral equations are based on random functional or stochastic equations, with the output that physical interpretation of the resulting fractional derivatives and fractional integrals has been elusive. In many different sciences and problems such as biological systems, environmental quality and natural resources engineering, and so on, stochastic equations and in some cases random functional have appeared. Despite the widespread use of stochastic fractional integro-differential equations (SFIDE), the analytical solution of this equation is not easy and in some cases it is impossible. Therefore, the existence of an efficient and appropriate numerical method can solve this problem. \vskip0.1cm In this study and based on fractional derivative in the Caputo sense, we investigate a class of SFIDE due to Brownian motion by using fractional B-spline basis functions (FB-spline) and with the help of the collocation-Galerkin method as well as the trapezoidal integral law. In other words, a continuous operator problem (here was named as SFIDE) is transformed into a discrete problem by limited sets of basis functions with common assumptions and approximation methods. In the follow-up a system of linear equations is generated, which makes the analysis of the method be efficient. As an important advantage of this combined method is its flexible and easy implementation. Another advantage of the method is its ability to be implemented for different types of linear, non-linear and system of SFIDE, which are discussed in the body of manuscript. An accurate upper bound is obtained and some theorems are established on the stability and convergence analysis. The computational cost is estimated from the sum of the number arithmetic operations and a lower bound for approximation of this equation is formulated. Finally,
