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Abstract Geomechanical analysis is fundamental to well planning and field development, ensuring operational safety and efficiency in the entire life cycle of the well. Traditional methods for constructing one-dimensional mechanical earth models (1D MEM) are time-intensive, requiring weeks of manual data handling and expert interpretation, with accuracy heavily dependent on complete and high-quality datasets. This study presents an integrated, machine learning (ML)-driven approach that automates the entire geomechanical workflow—from data import, quality control to generation of 1D MEM properties and wellbore stability analysis, reducing analysis time by over 90% and improving model accuracy through intelligent ML algorithms, ultimately enabling cleaner, safer, and more profitable drilling operations. The process starts with quality control and the detection of outliers via interquartile range (IQR) and isolation forest (IF) algorithms on multiple wells. The ML model fills in missing log segments and predicts any missing logs in the key wells employing the random forest regression algorithm based on training from the available wells. Rock mechanical properties are calculated by applying lithology-based industry-used formulations, and lithology is predicted with prediction errors of less than 10% using both supervised and unsupervised ML techniques. Automated normal compaction trend (NCT) generation based on shale formation is used for precise pore pressure prediction for target wells, calibrated against modular formation dynamics tester (MDT) / repeat formation tester (RFT) / drill stem test (DST) data. The subsequent 1D MEM properties are calculated using industry-standard equations that offer mud window planning and wellbore stability analysis. This ML-based solution is a paradigm shift in geomechanical analysis, cutting weeks of traditional workflows down to hours while preserving high accuracy through systematic calibration against field and core data, ultimately optimizing drilling operations and reducing non-productive time (NPT) in a range of geological settings.