The design of multiple coupled resonator filters (MCRF) with finite transmission zeros has received considerable attention in recent years due to their superior selectivity, compact size, and low insertion loss compared with traditional all pole filters. Furthermore, real transmission zeros can be placed at desired frequencies to completely suppress specific interference signals while complex transmission zeros can be synthesized to equalize the group delay. However, tuning and design of these filters is a tedious and time consuming task even for experienced filter designers. The main goal of this research is to develop an efficient CAD tool for synthesis, design, tuning, and diagnosis of MCRF’s. The thesis is divided into two parts: in the first part, the synthesis of single and dual band filters is addressed and, in the second part, an efficient method for tuning and diagnosis is presented. An analytic method is available to synthesize the polynomials for single band filters with arbitrary transmission zeros while an optimization based approach is adopted for synthesizing the polynomials for dual band filters. After calculating the initial coupling matrix from the scattering parameters, an eigenvalue based optimization technique is applied to reduce the initial coupling matrix to an appropriate form for the desired filter topology. In the process of tuning, physical dimensions of the filter are adjusted so that the desired frequency response is achieved, i.e. the correct values of cross couplings, direct couplings, input/output couplings, and resonance frequencies are implemented. Therefore, an accurate diagnosis technique is required in order to extract the above parameters from the filter response so that the engineer can adjust the physical parameters towards achieving the desired response. In this thesis, a robust and efficient model based parameter extraction (MBPE) technique is utilized to extract the coupling matrix from the filter response. The proposed method is very fast and robust and can be used, with good accuracy, for low loss filters. After collecting frequency samples of the filtering function either from measurements (post fabrication tuning) or from electromagnetic simulations (during the design process), the Cauchy method is used to fit a rational function to the data. In the case of lossy filters, the effect of loss is removed by properly shifting the zeros and poles of the filtering function, thus a lossless model is obtained. Finally, using the Feldkeller’s equation, Keywords: multiple coupled resonator filters (MCRF), coupling matrix, model based parameter extraction method (MBPE),Cauchy method.