Knowledge regarding the kinetics of metastatic tumor formation, as related to the growth of the primary tumor, represents a fundamental issue in cancer biology. Using an in vivo mammalian model, we show here that one can obtain useful information from the frequency distribution of the sizes of metastatic colonies in distant organs after serial sectioning and image reconstruction. To explain the experimental findings, we constructed a biophysical model based on the respective growth patterns of the primary tumor and metastases and a stochastic process of metastatic colony formation. Heterogeneous distributions of various biological parameters were considered. We found that the elementary assumption of exponential forms of growth for the primary tumor and metastatic colonies predicts a linear relation on a log-log plot of a metastatic colony size distribution, which was consistent with the experimental results. Furthermore, the slope of the curve signifies the ratio of growth rates of the primary and the metastases. Non-exponential (Gompertzian and logistic) tumor growth patterns were also incorporated into the theory to explain possible deviation from the log-log linear relation. The observed metastasis-free probability also supported the assumption of a time-dependent Poisson process. With this approach, we determined the mechanistic parameters governing the process of metastatogenesis in the lungs for two murine tumor cell lines (KHT and MCaK). Since biological parameters specified in the model could be obtained in the laboratory, a workable metastatic "assay" may be established for various malignancies and in turn contribute in formulating rational treatment regimens for subclinical metastases.