Abstract: With the advent of the digital age, algorithms increasingly dominate the development of various industries and the emergence of new sectors, giving rise to a digital economy-led industrial landscape. Metrology, as the science of measurement and its application, is rapidly entering the digital era, with the promotion of digital transformation in the metrology industry becoming a top priority. Consequently, evaluating the accuracy and reliability of algorithmic software outputs has become a focal point of current research. This paper employs a digital metrology method based on reference data, using the output of a leukemia recognition algorithm software applied to patient clinical test data as the measurement result. It establishes an evaluation model for the leukemia recognition algorithm, outlines the specific process for assessing measurement uncertainty, and calculates the combined standard uncertainty of the measurand.