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Purpose: Patient size‐specific dose estimate (SSDE) calculations require knowledge of a patient's size. Errors in patient size propagate through SSDE calculations. AAPM Reports 204 and 220 recommend that a magnification correction be applied to patient size surrogates extracted from CT localizer radiographs. This technical note presents a novel approach for such a magnification correction. Methods: In our model‐based magnification correction, we assume that the patient's cross sections are elliptical with minor and major axes defined using the anterior–posterior (AP) and lateral (LAT) patient dimensions. We parameterize the problem by modeling a line emanating from the source, grazing the patient (i.e., the ellipse), and then terminating onto the detector plane. We model tangent lines on each side of the ellipse on both the LAT and AP CT localizer radiographs. We also account for vertical mispositioning with table offset. We compared our correction model to the actual AP and LAT dimensions to the vendor‐supplied CT localizer images that only received a geometric magnification correction, and to other methods described in the literature. We compare our model to the others using direct size to size comparisons as well as SSDE conversion factor. Results: Our model‐based method provides consistent accurate results (less than 1.8% error for absolute size and 1.2% error for SSDE for all measurement conditions) for all positions and patient sizes. Existing literature‐based methods had maximum errors for absolute size and SSDE of 7.5% and 5.2%, and for the vendor, they were 30.9% and 17.0%, respectively. Conclusion: We presented a new model‐based geometric size correction method that outperforms a simple geometric correction as well as other methods presented in the literature. By modeling the patient cross section and beam geometry using information all derived from the DICOM header and CT localizer views, we demonstrated SSDE correction factor improvements from 17.0% (vendor correction) to 1.2% (model base). These changes correspond directly into changes in SSDE itself and also represent clinically realistic patient sizes and mispositioning amounts. [ABSTRACT FROM AUTHOR]