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The determination of photometric redshifts is essential for many subjects in cosmology and extragalactic astronomy, like the large scale structure of the Universe, gravitational lensing, or galaxy evolution. If the spectral energy distribution (SED) of a galaxy is measured with high enough spectral resolution, the redshift can be easily derived through the absorption and emission lines which are created by the elements in the galaxy. However, currently more telescopes are equipped with large cameras with charged coupled devices (CCDs) that observe the sky through optical filters. With these photometric observations it is possible to detect much fainter astronomical objects than with spectroscopy. Furthermore, photometric observations are less time consuming and cheaper in comparison, wherefore they are preferentially used for observations of statistical meaningful cosmological volumes. Nonetheless, photometric data, which are often gained by observations through broadband filters, are not as precisely resolved as spectra. Therefore one does not have information about the accurate position in wavelength of spectral lines, but only about the overall shape of the SED. This is the reason why so-called photometric redshifts have to be derived by statistical means.\nOne approach to estimate the redshift through photometry alone are template fitting methods which compare the fluxes predicted by model spectra with the observations. After that, a likelihood analysis is performed with which a probability density function P(z) and the most probable value of z can be derived. To achieve high accuracies with photometric redshift template fitting techniques, the model spectra as well as their corresponding prior probabilities have to be chosen carefully.\n\nIn this work I use photometric and spectroscopic data of luminous red galaxies from the Sloan Digital Sky Survey (SDSS). I analyze the precision of photometric redshifts estimated with model SEDs specifically designed to match the set of luminous red galaxies of SDSS-II at redshifts z \u2264 0.5 in color and I compare them with published results. These models were created without information on their properties at wavelengths shorter than the SDSS u band. However, the galaxy UV characteristics derived from the model SEDs match those of other observations. Furthermore, I investigate the SED properties derived from the best fitting models with respect to spectroscopic data as functions of redshift and luminosity. At lower redshifts less luminous galaxies from our sample on average show increased signs of star formation in comparison to galaxies with higher luminosities. This is supported by analyses of the line strengths in the spectra. Moreover, star formation activity increases with increasing redshift which is caused by the aging of the galaxy population from higher to lower redshifts.\n\nI also generate model spectra for red galaxies from the SDSS-III located at even higher redshifts 0.45 \u2264 z \u2264 0.9. For this I modify the shape of theoretical spectra to match the data of the analyzed galaxies to a better extent. The multidimensional space defined by the colors and the absolute magnitude of the galaxies is reduced to two dimensions through a self-organizing map. The map is then partitioned by a k-means algorithm which identifies clusters in the data. From the cluster cells I select model spectra which represent the galaxies from within the same cell. A selection of the models is then used as a template set for photometric redshift estimation. I find that our models improve the redshift accuracy in comparison to the results published by SDSS.