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Urban climate comfort is an indicator that is a reflection of a set of parameters such as temperature, humidity, and solar radiation on a person’s sensation of being favorable to being o outdoors or indoors. In this study the attempt to develop online technology of prediction of thermal comfort conditions in urban landscape is described (based on the example of Moscow State University campus). For this task authors used RayMan model-based algorithm for calculating three most popular worldwide comfort indexes: PET, UTCI, mPET. In frame of scripting method predictive data of the Canadian GEM global meteorological parameters were automatically transferred to Rayman-model (with deep implementation of unique MSU-campus landscape thermal and radiation properties) by using AutoClickExtreme autoclicker. For the convenience of perception of information, the results of calculations are visualized on the basis of OpenStreet maps. Thus, the main idea of the work was that any user with the minimum expenditure of his time resource and without knowledge of the model’s work could launch the program and receive an individual forecast of comfort conditions for the next hours in a visually understandable format. It is assumed that the developed methodology will be used for calculations on projected areas to identify the safest construction option. Such online forecasting will continue to be of particular importance for the functioning of urban infrastructure.