Each model approaches decision-making from a different mathematical perspective
EV = P(V)Calculate risk-adjusted expected outcomes using probability-weighted values
Backward InductionVisualize complex decisions with branching outcomes and find the optimal path
WS ModelScore options against weighted criteria with normalization and sensitivity analysis
P(H|E) = P(E|H)P(H)/P(E)Update beliefs with new evidence using probability theory
Templates and guidance for common life decisions
Job offers, promotions, career changes
Investments, major purchases, budgets
Relocation, relationships, education
Name your decision and add options to consider
Choose analysis types and input probabilities
View results with interactive visualizations
Get a unified recommendation with confidence score