Nowadays, accurate software effort and time estimation are one of the main challenges in the software engineering community. Correct and precise estimation plays an important role in successful software development and organization productivity. Constructive Cost Model (COCOMO) is an algorithmic model commonly used in estimating time and effort having four coefficients. From the last few decades, many researchers work on optimization of the COCOMO model by using naturally inspired algorithms. Such optimization algorithms help the software industry in predicting accurate and genuine values of cost and effort used for software project development and maintenance. In this paper, we are using a new meta-heuristic algorithm inspired by the strawberry plant for optimization of COCOMO effort estimation method. NASA 93 data set is used in the proposed approach. The Magnitude of Relative Error (MRE) and Mean Magnitude of Relative Error (MMRE) is evaluated. Experimental results of the proposed method with the COCOMO model shows a decline in MMRE to 23.8%.