Artificial Intelligence and Society are ever so increasingly connected, both in magnitude and in frequency. The very same holds true for history, particularly for economic and social history, that is now interpreting and studying the past with Machine Learning, in the form of Social Network Analysis, Time Series Analysis, or even yet Cluster Analysis. Applications of these tools in the historiographical field are indeed necessary to assess the full extent of the entanglement between historical-critical method and quantitative analysis (descriptive, inferential and generative). This book wishes to lay grounds in this very direction, by juxtaposing different ways of investigating economic history, also from a methodological perspective: the aforementioned Time Series Analysis, Environmental History, Accounting History, Financial History, particularly of ecclesiastic organizations (which in turn renders it Charity History).