Studies on historical contingency in community assembly suggest the possibility of alternative transient trajectories, alternative stable states, and compositional cycles. Theoretically, an assembly pathway can be regarded as a sequence of transitions from one community type to another, where both extinction of species from a local community and immigration of species from a regional species pool can trigger such transitions. Here, by combining a pairwise Maximum Entropy Model (pairwise MEM) and the Energy Landscape Analysis (ELA), I introduce a minimal framework to approximate and study the constraint of assembly processes in a data-driven manner. The parameters of a pairwise MEM can be inferred from a set of snapshots of species distribution data. The ELA allows us to analyze the landscape structure embedded in a fitted pairwise MEM, such as the composition of stable states, the basins of attraction of stable states, and the structure of the boundary between them. The “ecological energy landscape analysis” I introduce here will help us study historical contingency in a predictive manner and will allow us to predict a potential pathway from one community state to another, the importance of species in terms of its effect on landscape structure, or change in community function and stability along with environmental gradients.