December 2025 monthly summary for the Classiq/classiq-library work stream. Key feature delivered: Classical Shadows for Quantum State Prediction, implementing end-to-end data acquisition and prediction methodologies. This work provides a scalable approach to estimating quantum states, enabling more accurate modeling and evaluation of quantum circuits. No major bugs reported this month; ongoing maintenance and code quality improvements were performed. Overall impact: enhances predictive capabilities for quantum state estimation, enabling faster design iterations, improved modeling, and stronger confidence in downstream decision-making. Technologies/skills demonstrated: quantum computing concepts, implementation of classical shadows, data acquisition pipelines, prediction model development, git-based collaboration and repository maintenance.