Decision trees that solve themselves, inside Excel.
ModelChoice draws your decision tree on an Excel worksheet, takes its probabilities and payoffs from cells you can link to the rest of your model, and finds the best choice again every time an input changes. The same tree then gives you sixteen analyses: what could happen under each option, which estimates matter, how far each one can move before the answer changes, what better information is worth, and a one-page brief for the board.
ModelChoice turns the decision you would sketch on a whiteboard into a working model in Excel. You draw the choices and the uncertain outcomes, put the probabilities and payoffs in cells, and ModelChoice finds the best strategy and its expected value. Each analysis then answers a question the board will ask about it.
You draw it on the worksheet. ModelChoice places decision, chance and outcome nodes on the sheet as Excel shapes, and every probability and payoff is a real cell, so you can link it to your financial model or an assumptions sheet. Change any input and ModelChoice solves the tree again straight away by backward induction. There is no Run button.
Best choice: Retrofit the line · expected value $1,950,000. Retrofitting stays best while the chance the catalyst holds is above 33.3%.
Click a yellow cell and type a new value. Try 30% for the chance the catalyst holds.
The highest average is not the whole story. Growth-Stage Fund has the best expected value, $159.3M, and a 20% chance of losing $20.0M. Treasury Bonds pay $115.0M for certain.
Most spreadsheet decisions are made on the average alone. The Risk Profile report shows every possible payoff for each strategy and how likely it is, with the expected value, the worst and best case and the standard deviation side by side. The Cumulative Risk Profile gives the same picture as percentiles.
One-way sensitivity analysis varies each input across a range and shows how the expected value of every option responds. A tornado chart ranks the inputs by how far they swing the result, a spider chart shows the path of each one, and ModelChoice marks the point where the best choice changes.
Break the Decision finds, for every input, the exact value at which the best strategy flips to another one. A robustness score from 0 to 100 sums up how fragile the recommendation is, and a Monte Carlo test varies all the inputs together to estimate how often it would be wrong. It is the defensible answer to the board’s question: how confident are we?
Growth-Stage Fund is the best choice today, but only just. Select a row in the report to see what would change the answer.
If the High Success probability rises from 0.200 to 0.276, the best first choice becomes Early-Stage Fund instead of Growth-Stage Fund.
The expected value of perfect information (EVPI) is the most any study could be worth: what knowing the outcome before you decide would add. The expected value of imperfect information (EVII) is what a real test of known accuracy adds. ModelChoice works out both from the tree, so you can set them against the cost of the test before you commission it.
The example is the catalyst retrofit from section 01. A demonstration-reactor pilot costs $250,000 and is right 90% of the time when the catalyst holds and 85% when it does not.
The Decision Brief puts the analysis on one page: the recommendation and how robust it is, the expected value, the chance of a loss, the estimates that drive the result, the nearest threats and a plain-English summary. It is rebuilt in seconds when an input changes, and Export Brief to PDF writes it as a single page.
ModelChoice scales the weights to add up to 1.
Local Supplier scores best with these weights, 0.062 ahead of Dual Source.
Try Sustainability at 0% and Quality at 60%: Dual Source comes out on top.
Multi-criteria decision analysis (MCDA) scores each outcome on criteria such as quality, delivery, safety or sustainability as well as the financial payoff. You give each criterion a weight and a scale of named options, and ModelChoice works out a composite score at every outcome and rolls the tree back on it.
Some uncertainties are better described by a continuous distribution than by a few branches: a price, demand, a duration, an interest rate. With ModelRisk, Vose’s Monte Carlo add-in, you can put a distribution such as VosePERT, VoseNormal or VoseLognormal into any payoff or probability in the tree and simulate it thousands of times.
=VosePERT(300000000, 470000000, 700000000)
A fast estimate of the best strategy and its expected value when some inputs are continuous.
Each iteration follows one complete path through the tree and records its payoff, so you see the full spread of outcomes.
Each iteration picks the decision that would have been best for that iteration’s outcomes, giving the EVPI under continuous uncertainty.
Illustrative: a ModelRisk distribution typed into the Accelerate Growth payoff cell of the tree at the top of this page.
ModelChoice is an Excel add-in, not a separate application, so a tree lives next to the data that feeds it. Existing PrecisionTree models come across in one click, trees can be saved as JSON, and everything the ribbon does can be scripted.
The Import command converts a copy of a PrecisionTree workbook (.xls or .xlsx) into a native ModelChoice tree. The original is left untouched.
Save any tree, with its settings and MCDA set-up, as a JSON file. Keep it in version control, compare versions, or build trees from a database.
Headless commands for the main analyses, callable from Python, .NET or VBA through Application.Run, for batch runs and in-house tools.
Functions such as MC_NodeValue, MC_NodeDecision and MC_NodeProbability return a node’s value, decision or probability in any cell.
Key values are named ranges (MC_V_…, MC_P_…), every formula can be inspected, and sheet protection locks a finished model.
The open modelchoice-mcp server lets assistants such as Claude build and edit trees, import PrecisionTree models and run ModelChoice reports through conversation.
Ribbon, dialogs, messages and help in English, German, Spanish, French, Japanese, Portuguese and Russian.
Ready-to-run trees from oil and gas, pharma, finance, infrastructure, manufacturing, technology, agriculture and the public sector.
Everything on this page is included in every ModelChoice licence. Monte Carlo simulation also needs ModelRisk.
ModelChoice is sold as an annual licence, for a single computer or as a network licence, in one edition with every feature on this page included and a fully functional 15-day trial. Current prices and volume discounts are on the pricing page. Our comparison of seven decision analysis tools lists the prices other vendors publish.
No. ModelChoice works on its own in Excel. You need ModelRisk only if you want continuous distributions in the tree and a Monte Carlo simulation through it.
Yes. The Import command converts a copy of a PrecisionTree workbook (.xls or .xlsx) into a native ModelChoice tree and leaves the original untouched. Our PrecisionTree alternative guide compares the two products.
In your Excel workbook. ModelChoice draws the tree as Excel shapes next to the cells that hold its values, so it is saved, shared and version-controlled with the workbook, and colleagues without ModelChoice can still open it. You can also export any tree to JSON.
Microsoft Excel 2016, 2019, 2021 or Microsoft 365, 32-bit or 64-bit, on Windows 10 or 11, with the .NET 9 runtime. ModelChoice does not run on macOS. Full details are on the system requirements page.
Yes. The 15-day trial is the complete product, with every analysis and all 59 example models, so you can build your first tree on a decision you are working on.
The full product: draw a tree with your own numbers and see its risk profile, robustness score and Decision Brief. See prices and discounts