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Tax is one of the main sources of financing government budget. Therefore, having a clear picture about the attainable amount of taxes are not only necessary for optimal allocation of scarce resources for tax collection, but also helps the government to develop precise tax collection programs .In this article, the structural features of the tax revenues series have first been examined in relation to linearity, chaotic nonlinearity and stochasticity, using Lyapunov Exponent. These series are: total taxes, direct taxes, indirect taxes, corporate taxes, income taxes, salary taxes, real estates taxes, business taxes, wealth taxes, inheritance taxes and goods & services taxes. The results indicated the existence of a chaos in the series of different tax resources with different weakness and severity. Therefore, based on the results it was found that we can do more accurate short-term predictions by applying nonlinear modeling. In the next step, using the data of the period 1963-2006,the tax revenues of different resources were forecasted for the period 2007-2009 by applying both parallel and proposed Multiple-input Multiple-output structures of the ANN’s

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