There are several factors that can affect on the quality of construction and all of the using elements, such as mortars, as a basic component of the building industry, are effective in the ability and performance of the building. Therefore, determination of strength of mortar is an important property in construction and many studies have been done to identify the effective parameters and the predictive relationships to determine the strength of mortars. In this paper, the effect of two types of materials including micro-Silica and also Calcium Inosilicate minerals on the compressive strength of mortars has been investigated by artificial neural networks. Also, a suitable relationship to estimate the considered strength is proposed based on the selected neural network. The results of the relationships show that these equations with a high accuracy have a proper ability and acceptance performance to predict the compressive strength of considered mortars.