The paper introduces EAZY, a new program for determining photometric redshifts, designed to handle cases where spectroscopic redshifts are either unavailable or biased. EAZY combines features from various existing codes, including the ability to fit linear combinations of templates, use optional priors, and a user-friendly interface similar to HYPERZ. The default template set and priors are derived from semi-analytical models, addressing the limitations of spectroscopic samples. A novel feature is the template error function, which accounts for wavelength-dependent template mismatch, ensuring realistic redshift uncertainties. The code includes a redshift quality parameter, \(Q_z\), to estimate the reliability of photometric redshift estimates. Despite not being trained on spectroscopic samples, EAZY performs well on existing public datasets, with a 1σ scatter of 0.034 in \(\Delta z/(1+z)\) for \(K\)-selected samples in deep fields. The paper also discusses the implementation details, application to various photometric catalogs, and comparisons with spectroscopic redshifts, highlighting the reliability and performance of EAZY.The paper introduces EAZY, a new program for determining photometric redshifts, designed to handle cases where spectroscopic redshifts are either unavailable or biased. EAZY combines features from various existing codes, including the ability to fit linear combinations of templates, use optional priors, and a user-friendly interface similar to HYPERZ. The default template set and priors are derived from semi-analytical models, addressing the limitations of spectroscopic samples. A novel feature is the template error function, which accounts for wavelength-dependent template mismatch, ensuring realistic redshift uncertainties. The code includes a redshift quality parameter, \(Q_z\), to estimate the reliability of photometric redshift estimates. Despite not being trained on spectroscopic samples, EAZY performs well on existing public datasets, with a 1σ scatter of 0.034 in \(\Delta z/(1+z)\) for \(K\)-selected samples in deep fields. The paper also discusses the implementation details, application to various photometric catalogs, and comparisons with spectroscopic redshifts, highlighting the reliability and performance of EAZY.