Inventory control in a Supply chain is crucial for companies who wish to satisfy their customer demands on time as well as controlling costs. A common approach is to use the MRP techniques. However, these techniques are based on the supposition that lead times are known. In a Supply chain the lead times are often random variables. Therefore, an efficient exact approach to aid in MRP parameterization under lead time uncertainties was developed; more precisely the approach has as objective to calculate planned lead times when the component procurement times are random. The aim is to find the values of planned lead times which minimize the sum of the average component holding cost and the average backlogging cost. The developed approach is based on a mathematical model of this problem with discrete decision variables and on a Branch and Cut algorithm.