The study of galaxy evolution hinges on our ability to interpret multiwavelength galaxy observations in terms of their physical properties. To do this, we rely on spectral energy distribution (SED) models, which allow us to infer physical parameters from spectrophotometric data. In recent years, thanks to wide and deep multiwave band galaxy surveys, the volume of high-quality data have significantly increased. Alongside the increased data, algorithms performing SED fitting have improved, including better modeling prescriptions, newer templates, and more extensive sampling in wavelength space. We present a comprehensive analysis of different SED-fitting codes including their methods and output with the aim of measuring the uncertainties caused by the modeling assumptions. We apply 14 of the most commonly used SED-fitting codes on samples from the CANDELS photometric catalogs at z similar to 1 and z similar to 3. We find agreement on the stellar mass, while we observe some discrepancies in the star formation rate (SFR) and dust-attenuation results. To explore the differences and biases among the codes, we explore the impact of the various modeling assumptions as they are set in the codes (e.g., star formation histories, nebular, dust and active galactic nucleus models) on the derived stellar masses, SFRs, and A ( V ) values. We then assess the difference among the codes on the SFR-stellar mass relation and we measure the contribution to the uncertainties by the modeling choices (i.e., the modeling uncertainties) in stellar mass (similar to 0.1 dex), SFR (similar to 0.3 dex), and dust attenuation (similar to 0.3 mag). Finally, we present some resources summarizing best practices in SED fitting.