There is a consensus that time series model is not appropriate in forecasting replacement parts. However most of market used forecasting tools are time series models. This work presents Poisson distribution as an alternative to forecast replacement parts on electronic equipments. From basic stock management notions, using time series and trust concepts of reliability, availability, and Poisson Process, an alternative model is proposed. Using real examples, the result from proposed model and its comparison to SAGA model, which is based on time series, is presented. The major characteristic of the proposed model is the application of Poisson distribution, and the real faults rate as the main calculus parameters. The analyses results have shown that is possible to reduce forecasting errors, therefore the stock cost, and the reduction of back orders amount, increasing the Operational availability.