CT (Computed Tomography) – TDLAS (Tunable Diode Laser Absorption Spectroscopy) is a non-intrusive diagnostic technique that allows for spatially resolved measurements of temperature and species concentration combustion fields such as burners, engines, gas turbines and furnaces and so on. Also, temperature and concentration distribution on the cross-section of a combustion flame enable to analyze elaborately on the combustion phenomena. The main purpose of this work is to optimize a reconstruction of temperature and H2O number density distribution based on CT-TDLAS. In this study, the optimized MART (Multiplicative Algebraic Reconstruction Technique) method was proposed for the data reconstruction of CT-TDLAS and the results were compared with ART (Algebraic Reconstruction Technique) method. Also, MLOS (Multiple Line of Sight) method was suggested to decide optimal initial values for iterative calculation of CT-TDLAS. Finally three new signal fitting algorithms, Two-Ratios of Three-Wavelength Fitting algorithm, Full-Profile Cross-Correlation algorithm and 6-Line-Profiles Fitting algorithm, were proposed for reconstruction of temperature and concentration using TDLAS system and their reconstruction performances were quantitatively compared. Three types of algorithms were theoretically investigated by using virtual lasers and were demonstrated experimentally by utilizing the data obtained in a burner and an engine experiment in case of necessity. In conclusion, 6-Line-Profiles Fitting Algorithm was a very stable calculation and showed good agreement with the numerical and experimental data and Also, number density and temperature were possible to reconstruct simultaneously. it is expected that it enables to apply the real-time 2D temperature and species concentration measurement in various combustion fields.