Recalibrating the risk of false confession wrongful convictions: Interrogation tactics and inverse probability

False confession wrongful convictions (FCWCs) are a serious failure of the criminal justice system. Although scholars have identified interrogation tactics thought to elevate this risk, existing research rarely estimates the population-level probability that legally permissible methods will produce an FCWC. Instead, inference relies on outcome-selected case series and laboratory diagnosticity ratios that ignore base rates and the far larger universe of interrogations without false confessions. This article offers a methodological recalibration. We formalize the outcome-selection problem and apply inverse probability logic to derive posterior FCWC risk integrating base rates, sensitivity, and specificity. Using Monte Carlo simulation, we synthesize available empirical evidence across a wide parameter space. Across these specifications, median posterior estimates of the probability of a false confession wrongful conviction associated with lawful interrogation tactics cluster near 1 %. We conclude by introducing an Acceptability Curve that clarifies how normative judgments about tolerable error shape policy conclusions. • False confession wrongful convictions associated with lawful interrogation tactics are rare, with posterior medians near 1%. • Recalibrates FCWC risk using inverse probability and population base rates • Corrects outcome-selection bias in false confession research • Estimates posterior FCWC probabilities for legally permissible interrogation tactics • Links empirical risk estimates to policy thresholds via an acceptability curve