The initial goal of this study is to introduce and discuss the different startup valuation methods. Usually startups can t be valued through traditional methods such as discounted cash flow (DCF) and market multiples due to its lack of profits. Even when profits are present, uncertainty plays a big part on valuation, making it difficult and limiting the comprehension of the inherent business risks. Due to the limitations of traditional valuation methods, this dissertation suggests adding uncertainty to the traditional models through stochastic variables present in the valuation, thus allowing the investor not only to look at the potential gains, but also at the potential losses and its probabilities. We also look at real options present in startup shareholders agreement. The results are shown as a real case study. Finally, in the outcomes discussion and in the conclusion, we compare the methods, discussing its advantages and disadvantages, where we expect to demonstrate the superiority of the stochastic method for valuying startups.