Chromosomal instability (CIN) increases a tumor cell's ability to acquire chromosomal alterations, a mechanism by which tumor cells evolve, adapt, and resist therapeutics. We sought to develop a biomarker of CIN in circulating tumor cells (CTC) that are more likely to reflect the genetic diversity of patient's disease than a single-site biopsy and be assessed rapidly so as to inform treatment management decisions in real time. Large-scale transitions (LST) are genomic alterations defined as chromosomal breakages that generate chromosomal gains or losses of greater than or equal to10 Mb. Here we studied the relationship between the number of LST in an individual CTC determined by direct sequencing and morphologic features of the cells. This relationship was then used to develop a computer vision algorithm that utilizes CTC image features to predict the presence of a high (9 or more) versus low (8 or fewer) LST number in a single cell. As LSTs are a primary functional component of homologous recombination deficient cellular phenotypes, the image-based algorithm was studied prospectively on 10,240 CTCs in 367 blood samples obtained from 294 patients with progressing metastatic castration-resistant prostate cancer taken prior to starting a standard-of-care approved therapy. The resultant computer vision-based biomarker of CIN in CTCs in a pretreatment sample strongly associated with poor overall survival times in patients treated with androgen receptor signaling inhibitors and taxanes. SIGNIFICANCE: A rapidly assessable biomarker of chromosomal instability in CTC is associated with poor outcomes when detected in men with progressing mCRPC.