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Finding the Missing: How AI, Data Analysis, and Monte Carlo Simulation Can Predict Disappearances, Recover Victims, and Solve Cold Cases
Finding the Missing
How AI, Data Analysis, and Monte Carlo Simulation Can Predict Disappearances, Recover Victims, and Solve Cold Cases
Every year, hundreds of thousands of people disappear—and too many cases go cold not because of a lack of effort, but because of fragmented data, fading time windows, and human limits under uncertainty.
Finding the Missing reveals how artificial intelligence, advanced data analysis, and probabilistic modeling are reshaping the investigation of missing persons—without replacing human judgment or compassion.
This book goes beyond sensational true crime and speculative technology. Instead, it offers a grounded, investigative framework for turning chaos into transforming narrative reports into analyzable data, identifying hidden behavioral and geographic patterns, and using Monte Carlo simulations to model movement, risk, and search probability under real-world uncertainty.
Readers will learn how modern decision-support systems
Prioritize missing-person cases when resources are limited
Generate evolving probability maps to guide search and recovery
Detect meaningful patterns without false accusations or narrative bias
Estimate survival likelihoods responsibly—without fatalism
Revisit cold cases when new data shifts long-standing assumptions
Rather than treating AI as a “predictive oracle,” Finding the Missing shows how technology works best as a partner—helping investigators ask better questions, reduce blind spots, and defend decisions years later with transparent, auditable logic.
The book also confronts the ethical realities algorithmic bias, surveillance creep, data misuse, and the danger of false certainty in life-and-death investigations. Clear boundaries are drawn around what AI should never decide alone—and how human-in-the-loop systems protect both justice and dignity.
Written for investigators, analysts, search-and-rescue professionals, policymakers, technologists, and serious true-crime readers, Finding the Missing offers a sober, practical roadmap for applying data science where it matters most.
This is not a book about predicting tragedy.
It is a book about using probability to restore focus, clarity, and hope—when time matters most.
How AI, Data Analysis, and Monte Carlo Simulation Can Predict Disappearances, Recover Victims, and Solve Cold Cases
Every year, hundreds of thousands of people disappear—and too many cases go cold not because of a lack of effort, but because of fragmented data, fading time windows, and human limits under uncertainty.
Finding the Missing reveals how artificial intelligence, advanced data analysis, and probabilistic modeling are reshaping the investigation of missing persons—without replacing human judgment or compassion.
This book goes beyond sensational true crime and speculative technology. Instead, it offers a grounded, investigative framework for turning chaos into transforming narrative reports into analyzable data, identifying hidden behavioral and geographic patterns, and using Monte Carlo simulations to model movement, risk, and search probability under real-world uncertainty.
Readers will learn how modern decision-support systems
Prioritize missing-person cases when resources are limited
Generate evolving probability maps to guide search and recovery
Detect meaningful patterns without false accusations or narrative bias
Estimate survival likelihoods responsibly—without fatalism
Revisit cold cases when new data shifts long-standing assumptions
Rather than treating AI as a “predictive oracle,” Finding the Missing shows how technology works best as a partner—helping investigators ask better questions, reduce blind spots, and defend decisions years later with transparent, auditable logic.
The book also confronts the ethical realities algorithmic bias, surveillance creep, data misuse, and the danger of false certainty in life-and-death investigations. Clear boundaries are drawn around what AI should never decide alone—and how human-in-the-loop systems protect both justice and dignity.
Written for investigators, analysts, search-and-rescue professionals, policymakers, technologists, and serious true-crime readers, Finding the Missing offers a sober, practical roadmap for applying data science where it matters most.
This is not a book about predicting tragedy.
It is a book about using probability to restore focus, clarity, and hope—when time matters most.
267 pages, Kindle Edition
Published January 7, 2026
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