Ransomware attacks have rapidly emerged as crippling threats to organizational stability and business continuity. This study conducts an in-depth analysis of real-world phishing emails that often initiate ransomware deployments within companies. The key objectives encompass identifying psychological tricks, technical deceits and language anomalies commonly conveyed in such emails to better inform defensive strategies. Additionally, a ChatGPT-powered machine learning model is designed using natural language processing for automatically detecting ransomware phishing attempts. The findings reveal manipulative patterns regarding urgency triggers, security-related technical terminologies, and language inconsistencies that distinguish malicious emails from authentic communications. The model demonstrates high accuracy levels in categorizing phishing emails, serving as a swift automated layer of security against cunning ransomware infiltration.