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Digital Filters play a vital role in digital signal processing.They are preferred in comparison to analog filters due to various advantages like linear phase response and higher stop band attenuation.In category of Digital filters, FIR filters are a suitable choice since they introduce no phase distortion and suffer less from the effects of round off noise and coefficient quantization errors. The traditional FIR filter design methods are window method, Parks-McClellan method. The main limitation of these method is that they does not results in the optimum FIR filter as they does not permit individual control over the approximation errors in various band.This thesis focuses on the application of computational intelligence (CI) techniques for Digital FIR filter design. Computational intelligence techniques have been widely used in the digital filter design than the traditional design methods because they provide better parameter control and better approximation to the ideal filter.Since stochastic search methods have proven to be effective in multidimensional nonlinear environment,all of the constraints of filter design can be effectively taken care of by the use of these algorithms.