Clinical decision-making for elderly cancer patients has long relied on crude generalizations about age and treatment tolerance, often leading to either overtreatment or therapeutic nihilism. The quest for precise mortality prediction tools represents a fundamental shift toward personalized oncology for the growing population of adults diagnosed with cancer after age 65. This systematic review from The Lancet Healthy Longevity examined 250 studies containing mortality prediction models specifically designed for older cancer patients, revealing significant methodological shortcomings across the field. Only 182 studies performed internal validation of their models, and the authors identified pervasive bias issues that compromise the reliability of existing prediction frameworks. The review synthesized models attempting to forecast both cancer-specific survival and all-cause mortality, recognizing that older adults face competing health risks beyond their malignancy. These findings expose a critical gap between the clinical need for accurate prognostic tools and the quality of available evidence. Oncologists treating elderly patients currently lack robust, validated instruments to guide treatment intensity decisions, estimate life expectancy, or facilitate informed discussions about goals of care. The high bias risk identified across existing models suggests that current prediction tools may systematically over- or underestimate mortality risk in this vulnerable population. For health-conscious older adults facing cancer diagnoses, this analysis underscores the importance of seeking care from oncologists who acknowledge prognostic uncertainty rather than relying on potentially flawed algorithmic predictions. The research highlights an urgent need for methodologically rigorous studies that can produce unbiased prediction models, potentially incorporating geriatric assessment tools, functional status measures, and comorbidity indices specifically calibrated for older adults with malignancies.