Cash flow forecasting is a critical aspect of financial planning and has long been of inter34 est to investors and creditors. The Gray Box (GB) method is a widely used tool for 35 forecasting, but a significant challenge in developing a grey box model is parameter esti36 mation. In this study, we introduce a novel approach to cash flow forecasting called the 37 Grey Wolf Optimization-based Grey Box model (GWOGB). The GWOGB employs a 38 GWO algorithm as a global search method to determine the parameters of the GB model. ∗Corresponding author. 1 Page Proof February 25, 2025 12:26 WSPC/S0219-6220 173-IJITDM 2550008 2 A. Ahmadi et al. 1 To enhance the accuracy of future cash flow forecasting, we incorporate firm-level control 2 variables as well as market and financial control variables into the classical model. To 3 evaluate the performance of the proposed model, we use a sample of 250 firms listed on 4 the Tehran Stock Exchange. Our empirical findings indicate that the GWOGB outper5 forms the generalized method of moments (GMM). Additionally, we employ sensitivity 6 analysis to discern the source of forecast error and find that the inclusion of the nonlinear 7 effect of sales growth rate on working capital accruals and future cash flow significantly 8 reduces forecast error. The results show that using a nonlinear form of the GWOGB 9 model is a promising approach for modeling the complex relationships between cash 10 flow and working capital accruals.

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