The important role in project management is to estimate the software effort. Inaccurate results may cause to over or under in estimating effort, which can have afflictive outcome on the resources of project. The Constructive Cost Model (COCOMO II) is one of the most mathematical models widely and known for estimating software effort which is influenced by two parameters. To estimate these parameters, there are many techniques used for this purpose. The optimized model produces optimal parameters to estimate the software effort. In this paper, a hybrid model of ant-lion optimization algorithm and cuttlefish algorithm (HALOCF) have been proposed for optimizing two parameters of COCOMO II to solve the parameters estimation problem. The proposed model is performed using two sets of data: NASA 93 and NASA 60 datasets to verify the accuracy of it and evaluated by using Magnitude of Relative Error (MMRE). The results showed that the effort estimation MMRE for the proposed model is more effective than COCOMO II and many other technologies