Breast cancer remains the most prevalent malignancy among women and a leading cause of cancer-related death, primarily due to metastatic progression. Reliable preclinical models that recapitulate the metastatic cascade are essential for understanding disease mechanisms and evaluating novel therapies. Traditional methods, while informative, often lack the sensitivity and dynamic resolution needed to track metastatic spread in vivo . This study demonstrates the utility of integrating in vivo optical digital image analysis with histopathological digital image analysis to enhance the detection, characterization, and translational relevance of patient-derived xenograft (PDX) models of metastatic breast cancer. The metastatic potential of three breast cancer models first was classified in-vitro using two assays: 2D scratch wound and 3D spheroid invasion. Next, five PDX models, composed of two Her2+(1162, 1322) and three triple negative models (401, 857, 1387), were developed and evaluated for spontaneous in-vivo metastasis in mice. The breast cancer cell line MDAMB231 served as positive control. To enable in vivo tracking, tumor cells were infected with a fluorescent reporter or a bioluminescent reporter (luciferase) and visualized using optical imaging systems (IVIS Lumina S5 and Licor Pearl). In the in-vitro assays, MDAMB231, MCF-7, and 401 (triple negative PDX) were classified as high, low, and non-metastatic respectively. In the in-vivo lung metastasis assay, two triple negative models (401, 1387) and one HER2+ model (1387) were classified as low-metastatic. The other triple negative model (1162) and HER2+ model (1162) displayed no metastases at all. Unfortunately, it was not possible to create a PDX with a reporter that was stably expressed because the reporters reduced with passages over time. However, these results demonstrate that transient transfection is a promising tool to follow tumor growth in vivo. Finally, the organs were harvested, and metastases were evaluated via histology (H&E) and human-specific immunohistochemistry (IHC, hLaminB1). The hLaminB1+ metastasis were quantified by digital image analysis (DIA) using the Visiopharm software. MDAMB231 metastasized mainly to the lung and to a lower extend to the liver and the brain. Its metastatic level was much higher than all the PDXs, reflecting the aggressive growth of the cell line. The DIA provided a robust interpretation of the PDX models, illustrating that this integrated workflow supports the selection and quantification of metastatic models, with applications in therapeutic testing and mechanistic studies.