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The increasing prevalence of Internet of Things (IoT) devices has introduced significant challenges in digital forensic investigations, requiring new strategies for effective evidence prioritization and analysis. Traditional forensic methods struggle with data heterogeneity, volatility, and legal constraints, making IoT evidence collection complex and time-sensitive. This paper presents a weighted prioritization model (WPM) that ranks IoT devices based on six forensic criteria, enabling investigators to focus on highpriority evidence first, reducing data loss and optimizing forensic workflows. Through case studies in arson, homicide, and missing person investigations, we demonstrate how WPM enhances investigative decisionmaking and resource allocation in real-world forensic scenarios. The proposed framework offers a structured, scalable, and adaptable approach to IoT forensic investigations, improving efficiency, reliability, and legal compliance in digital evidence collection.