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We propose a heuristic combination of conventional lumped de-embedding models [i.e., open-short (OS) and short-open (SO)] that is equivalent to a distributed model. The technique was named geometric-mean de-embedding (GM-DE), as it converges to the geometric mean of the two other methods for the single-port case. This is unlike existing distributed methods, which are often overly complicated, require additional dedicated calibration steps, and therefore have not been adopted in common practice. While lumped de-embedding has remained the mainstream method for more than three decades, our approach provides a practical yet robust pathway toward distributed deembedding. This is of utmost importance for accurate parameter extraction of RF HEMTs, particularly for the correct estimation of key performance figures like f max .