We provide theoretical explanation for the acquisition of numeral classifiers (sortal classifiers) and measure words (mensural classifiers) in Mandarin Chinese. Previous research in various languages separately observed that the general classifier is acquired before specific classifiers and that classifiers are acquired previous to measure words. However no theoretical discussion was fully developed and no study combined general classifier, specific classifiers and measure words in one dataset. We propose to fill these gaps by combining semantic complexity (Brown, 1973) and a mathematical approach (Her, 2012): given that the relative complexity of x, y and z is unknown, x + y is more complex than either x or y, and x + y + z is more complex than any of them. By applying the mathematical approach, it is observed that general classifier carries the mathematical value of times one, noted x, while specific classifiers posses x plus a semantic value of y, which highlights an inherent feature of the referent. Finally, measure words detain both x and y, along with a new information of quantity z. Therefore, the acquisition order is expected to start from the simplest semanticity and develop toward the most complex, i.e. general classifiers (x) > specific classifier (x+y)> measure word (x+y+z). As supporting evidence, we gathered longitudinal data from CHILDES (Child Language Data Exchange System; Zhou, 2008). The participants included 110 children from 1-6 years old, providing a total of 110 conversations of 20 minutes each with 1851 tokens of numeral classifiers and measure words. Our methodology applied the definition of acquisition from Brown (1973) and the equation of Suppliance in Obligatory Context (SOC) cross-checked with Target-Like Usage (TLU) from Pica (1983). The results demonstrated that our model generated correct prediction, serving as theoretical basis for future studies in the field of language acquisition.