There are many types of decision models that can be used for various purposes and situations. For instance, decision trees are graphical models that illustrate the sequential structure of a decision problem, the probabilities and payoffs of each branch, and the expected value of each alternative. Additionally, decision matrices are tabular models that demonstrate the performance of each alternative on each criterion, the weights of each criterion, and the overall score of each alternative. Influence diagrams are graphical models that show the causal relationships between the decision variables, uncertain events, and outcomes, along with the value of each outcome. Furthermore, Multi-criteria decision analysis (MCDA) is a family of methods that combine qualitative and quantitative criteria and preferences to rank or select the best alternative. Finally, Analytic hierarchy process (AHP) is a specific MCDA method that uses pairwise comparisons and hierarchical structures to determine the weights and scores of criteria and alternatives. These are just some examples of decision models that you can use or modify for your own decision problems. Depending on your context and needs, you may also use other types of models or combine them to create an even more comprehensive and reliable decision model.