Opto-acoustic imaging involves using light to produce sound waves for visualizing blood in biological tissue. By using multiple optical wavelengths, diagnostic images of blood oxygen saturation and total hemoglobin are generated using endogenous optical contrast, without injection of any external contrast agent and without using any ionizing radiation. The technology has been used in recent clinical studies for diagnosis of breast cancer to help distinguish benign from malignant lesions, potentially reducing the need for biopsy through improved diagnostic imaging accuracy. To enable this application, techniques for mapping oxygen saturation differences within tissue are necessary. Using biologically relevant opto-acoustic phantoms, we analyze the ability of an opto-acoustic imaging system to display colorized parametric maps that are generated using a statistical mapping approach. To mimic breast tissue, a material with closely matching properties for optical absorption, optical scattering, acoustic attenuation, and speed of sound is used. The phantoms include two vessels filled with whole blood at oxygen saturation levels determined using a sensor-based approach. A flow system with gas-mixer and membrane oxygenator adjusts the oxygen saturation of each vessel independently. Datasets are collected with an investigational Imagio^® breast imaging system. We examine the ability to distinguish vessels as the oxygen saturation level and imaging depth are varied. At depth of 15 mm and hematocrit of 42%, a sufficient level of contrast to distinguish between two 1.6-mm diameter vessels was measured for an oxygen saturation difference of ∼4.6  %  . In addition, an oxygenated vessel was visible at a depth of 48 mm using an optical wavelength of 1064 nm, and a deoxygenated vessel was visible to a depth of 42 mm with 757 nm. The results provide insight toward using color mapped opto-acoustic images for diagnosing breast cancer.