Which AWS service would be best suited for predictive analytics based on historical data?

The best choice for performing predictive analytics based on historical data is Amazon Forecast. This service is explicitly designed to leverage machine learning to generate forecasts based on historical time-series data. It automates the process of identifying patterns within the data, such as trends and seasonality, to generate accurate predictions for future values.

Amazon Forecast can ingest various data inputs, including historical demand, events, and related datasets, making it particularly effective for predicting future outcomes like product demand or resource utilization. It offers built-in algorithms and is tailored for predictive analytics, which aligns perfectly with the requirements of the question.

In contrast, the other services serve different purposes. Amazon Comprehend focuses on natural language processing to gain insights from unstructured text. Amazon SageMaker is primarily a machine learning platform that enables the development and deployment of machine learning models, but it does not specialize in time-series forecasting. Amazon Transcribe is designed for converting speech to text, which doesn't pertain to predictive analytics. Therefore, among the given options, Amazon Forecast stands out as the ideal service for the task mentioned.