In daily life events, there are many complexities arising from lack of information and uncertainty. Fuzzy linear programming approach has been developed to reduce or eliminate this complexity. This approach is the process of choosing the optimum solution from among the decision alternatives to achieve a specific purpose in cases where the information is not certain. One of the fields where uncertainty or the lack of information makes it difficult to decide is financial markets. Investors who have a certain amount of accumulations aim to increase in various ways as well as protecting the value of their income. While doing this, investors face the challenge of deciding to what extent they should invest in which investment instrument. Therefore, investors use fuzzy linear programming approach to eliminate this uncertainty and to create the optimal portfolio. In the proposed methods for the portfolio selection process in the literature, the weights of the criteria are calculated by using triangular fuzzy numbers. In this study, as an alternative to the Enea and Piazza's portfolio selection model, which uses the triangular fuzzy numbers for criteria weighting, a new model that uses the trapezoidal fuzzy numbers for the same aim was proposed. With the solution of the linear programming model which is based on the determined weights, an alternative solution has been produced to the problem of which investment instrument will be invested at what proportion. The results regarding to the proposed and the existing method in the literature were compared.