We construct a stochastic model of real estate pricing. The method of the pricing construction is based on a sequential comparison of the supply prices. We proof that under standard assumptions imposed upon the comparison coefficients there exists an unique non-degenerated limit in distribution and this limit has the Log Normal law of distribution. The accordance of empirical distributions of prices to the theoretically obtained Log Normal distribution we verify by numerous statistical data of real estate prices from Saint-Petersburg (Russia). For establishing this accordance we essentially apply the efficient and sensitive test of fit of Kolmogorov-Smirnov. Basing on the world admitted standard of estimation prices in real estate market, we conclude that the most probable price, i.e. mode of distribution, is correctly and uniquely determined under the Log Normal approximation. Since the mean value of Log Normal distribution exceeds the mode - most probable value, it follows that the prices valued by the mathematical expectation are systematically overstated. © 2016, North Atlantic University Union NAUN. All rights reserved.