Landscape quality evaluations generally refer to key role of natural and artificial elements of landscape in satisfaction and perception of landscape aesthetic. The purpose of article is the aesthetic quality evaluation modeling of landscape using artificial neural network in order to clarify existing rules in the landscape structure and relations of landscape elements with its aesthetic quality. To perform the study, four parks (Jamshidieh, Gheytarieh, Nahjolbalaghe, Aboatash) with variety in landscape quality and landscape design practices were chosen in Tehran. In this study, in order to model the aesthetic quality evaluation of landscape, structural features and landscape elements were recorded and aesthetic quality of landscape was classified in three classes of undesirable, desirable and extremely desirable aesthetic quality. Multilayer Perceptron network was used to data processing with artificial neural network. Considering network coefficients of determination which equal 0.88, 0.86, 0.99 in 1 to 3 classes, the accuracy of artificial neural network in aesthetic quality of landscape is assessed in extremely desirable level. Sensitivity analysis respectively prioritizes landscaping materials, mountain or rock and vegetation application to achieve desirable quality of landscape in parks designing. In landscapes, with extremely desirable aesthetic quality, structural features, consist of landscape composition and appearance, play a significant role in aesthetic quality of landscape determination.