Which level of biological organization gives the best forecast of evolutionary change? Which gives the most reliable handle for intervention? We argue these questions have different answers. Using a simulation study spanning six evolutionary regimes—random genetic drift, directional selection, Moran dynamics, frequency-dependent selection, eco-evolutionary feedback, and group-structured selection—we evaluate four biologically motivated description levels (gene composition, lineage composition, organism-level fitness, and an organism-plus-ecology summary) as predictors of four evolutionary targets, and four level-targeted interventions for their causal effects on the same targets. We identify 9 dissociation cells in which the level achieving the highest cross-validated predictive score differs from the level whose targeted perturbation produces the largest causal effect on the same outcome. The clearest mechanistic case is eco-evolutionary feedback on the resource target: the organism-plus-ecology summary achieves R² = 0.483 [0.473, 0.491] for future resource state, yet a gene-level intervention is the only perturbation that reliably alters resource state, and does so negatively (gap = −0.008 [−0.009, −0.008]) because the favored allele carries the highest per-capita consumption rate. Across all 9 dissociation cells, gene-level interventions dominate causally while higher-level summaries dominate predictively. We conclude that identifying the best-predicting level and identifying the best-intervening level are distinct empirical questions, and both are necessary for a complete account of multilevel evolutionary dynamics.