Approximately 30% of patients with chronic myelomonocytic leukemia (CMML) undergo transformation to a chemo-refractory blastic phase (BP-CMML). Seeking novel therapeutic approaches, we profiled blast transcriptomes from 42 BP-CMMLs, observing extensive transcriptional heterogeneity and poor alignment to current acute myeloid leukemia (AML) classifications. BP-CMMLs display distinctive transcriptomic profiles, including enrichment for quiescence and variability in drug response signatures. Integrating clinical, immunophenotype, and transcriptome parameters, Random Forest unsupervised clustering distinguishes immature and mature subtypes characterized by differential expression of transcriptional modules, oncogenes, apoptotic regulators, and patterns of surface marker expression. Subtypes differ in predicted response to AML drugs, validated ex vivo in primary samples. Iteratively refined stratification resolves a classification structure comprising five subtypes along a maturation spectrum, predictive of response to novel agents including consistent patterns for receptor tyrosine kinase (RTK), cyclin-dependent kinase (CDK), mechanistic target of rapamycin (MTOR), and mitogen-activated protein kinase (MAPK) inhibitors. Finally, we generate a prototype decision tree to stratify BP-CMML with high specificity and sensitivity, requiring validation but with potential clinical applicability to guide personalized drug selection for improved outcomes.