Predictive_Data_AT is a comprehensive R‑based workflow that guides users through the full lifecycle of preparing a raw dataset for predictive modeling. The script automates essential preprocessing tasks, including directory setup, data import, sampling, missing‑value detection, blank‑to‑NA conversion, factor re‑encoding, and multi‑stage imputation using mean, mode, and interpolation strategies. It also generates detailed exploratory summaries and descriptive statistics such as central tendency, dispersion, skewness, and kurtosis to help users evaluate the effects of cleaning and imputation on data structure and distribution. This framework provides a reproducible, pedagogically structured template for developing data literacy, ensuring data integrity, and preparing high‑quality inputs for downstream predictive analytics.