— Operations Research has three major methods called Mathematical Programming Techniques, Stochastic Process Techniques and Statistical Methods. Mathematical Programming plays a vital role among them. This programming has too many branches. Stochastic Programming is one of these branches. Non-linear programming algorithms are classified into two algorithms. They are unconstrained and constrained nonlinear algorithms. In general, there is no algorithm for handling nonlinear models, mainly because of the irregular behaviour of the nonlinear functions. Perhaps the most general result applicable to the problem is the Kuhn Tucker conditions. In constrained non-linear algorithms, stochastic programming techniques solve the non-linear problem by dealing with one or more linear problems that are extracted from the original program. This paper deals with basic concepts in stochastic linear programming. There are two techniques viz. two stage programming and chance constrained programming with an example which is solved in a computer in the Pascal Language.