Cancer-associated thrombosis (CT) carries a high, heterogeneous, and poorly predicted likelihood of mortality. Thus, we aimed to define predictors of 30-day mortality in 10,025 patients with CT. In a randomly selected derivation cohort, we used recursive partitioning analysis to detect variables that select for a risk of mortality within 30 days. In a validation cohort, we evaluated our results using Cochran-Armitage test. The most common types of cancer were lung (16%), breast (14%), and colorectal (14%); median age was 69 years (range, 14-101); most had metastatic disease (63%); 13% of patients died within 30 days. In the derivation cohort (n ¼ 6,660), a white blood cell (WBC) count in the highest quartile predicted early mortality (odds ratio, 7.8; 95% confidence interval [CI], 4.6-13.1); and the presence of metastatic disease, pulmonary embolism (PE), and immobility defined the risk of those with normal WBC count. We defined death risk according four sequential questions: (1) (Yes, group C; no, group B). In the validation cohort (n ¼ 3,365), the 30-day risk of death was 2.9% in group A (95% CI, 1.9-4.3), compared with 25% in group D (95% CI, 22.5-27.5), and there was a rate escalation between groups (p for trend < 0.01). In conclusion, with four sequential questions, the risk of death in CT can be easily stratified. An elevated WBC count at baseline predicted 30-day mortality better than metastases, PE, or immobility.