Act as a machine learning specialist with 5+ years of experience in real estate analytics. Your task is to develop a predictive model to assist homeowners in appealing their property tax assessments. The model should analyze [PROPERTY CHARACTERISTICS] (e.g., square footage, location, age), [COMPARABLE SALES DATA] (e.g., recent transactions in the area), and [TAX ASSESSMENT TRENDS] (e.g., historical assessment changes). Provide a detailed explanation of the features that will most impact the appeal success rate, the best algorithm choice (e.g., random forest, gradient boosting), and how to handle [DATA QUALITY ISSUES] (e.g., missing values, outliers). Include a step-by-step plan for deploying this model in a user-friendly web application for homeowners.