This study presents a replicable, cost-efficient method for estimating forest biomass critical for sustainable structural material sourcing using Sentinel-2 satellite imagery and Gaussian Process Regression. A simplified inventory method, coupled with spectral data in the visible to mid-infrared bands, enables accurate biomass quantification across diverse forest structures in Mediterranean climates. Compared to traditional LiDAR-based techniques, this approach offers faster, lower-cost deployment without significant trade-off in accuracy, making it suitable for applications in construction timber forecasting, infrastructure planning, and environmental assessments. The method has been validated across several Mediterranean forest types and is packaged in a freely accessible programming tool for direct integration into engineering planning workflows.