Even though sand-casting process is one of the oldest techniques to produce different products, the method is known as process of uncertainty since it is difficult to control process parameter and identify the real cause for defects associated to the process. Most defects encountered during casting identifies after the process is completed and then it leads to remelting and wastage of material, time and manpower. Currently modern casting foundries utilizes a significant effort to understand the underlying physics involved in solidification casting process to and to model casting process. However, local foundries used floor trial method to eliminate casting defects that leads to less productivity and decrease competitiveness in the market.rnThe main purpose of this study is to numerically model the solidification heat transfer during sand-casting process in case of Akaki Basic Metal Industry (ABMI). The model employs finite element method (FEM) utilizing fixed mesh technique. Computational simulation of the problem modeled using ANSYS software. Three cases selected from the foundry, casting of ash cleaner door and manhole cover by grey cast iron and casting of aluminum flywheel. The actual density of sand mold measured experimentally using analytical balance as 2506 kg/m3.rnThe simulation of a two-dimensional transient thermal analysis result shows the temperature distribution, heat flux distribution and nodal values. The result of the simulation depicts the total solidification times are 2249, 177, and 133 seconds for case 1, case, 2 and case 3 simulation. Besides parametric study analysis was performed to investigate the effect of mold size, pouring temperature and mold property on the cooling of solidification. Validation of results with experimental literature shows a good agreement with experimental literature data.rnThe study result can be an input to the foundry for controlling process parameters without performing actual casting in the floor. The study recommends that local foundries could give attention in using numerical models to predict the casting process in order to increase their productivity and competitiveness.