This paper presents a model reduction algorithm motivated by a connection between frequency domain projection methods and approximation of truncated balanced realizations. The method produces guaranteed passive models, has near-optimal error properties, is computationally simple to implement, contains error estimators, and can incorporate frequency weighting information in a straightforward manner. Examples are shown to prove that the method can outperform the standard order reduction techniques by providing similar accuracy with lower models or superior accuracy for the same size model.