Offer of Judgment Analyzer Guide for Arizona

7 min read

Published March 22, 2026 • By DocketMath Team

What this calculator does

Run this scenario in DocketMath using the Offer Of Judgment Analyzer calculator.

DocketMath’s Offer of Judgment Analyzer (Arizona) helps you evaluate an offer of judgment under A.R.S. § 12-1501 by turning case inputs into a structured estimate of potential outcomes—especially the cost-shifting / fee-shifting impacts that often drive settlement leverage.

This guide focuses on Arizona’s offer-of-judgment framework and maps the typical “decision points” you’ll see in practice: when an offer can be made, when it can be accepted, and what the timing rules mean for the defendant’s ability to use the statute effectively.

Note: This is a calculation and analysis guide, not legal advice. Offer-of-judgment results can depend on case-specific facts (like what counts as a “judgment,” how the parties framed the offer, and whether acceptance occurred within the statute’s requirements).

When to use it

Use this tool when you’re assessing whether an offer of judgment is worth making—or worth accepting—under Arizona law.

Typical triggers:

  • You’re within the settlement window and want to model “if accepted” vs. “if rejected.”
  • You’re preparing an offer and want to sanity-check the timing requirement: the offer must be made more than 30 days before trial begins.
  • You’re trying to understand whether the defendant’s offer can satisfy the statutory good faith requirement.
  • You want a repeatable approach for comparing different settlement numbers across multiple offers.

A practical rule from A.R.S. § 12-1501(A):

  • An offer may be made at any time more than 30 days before the trial begins (and it must not be accompanied by a stipulation for dismissal of the action).
  • If the offer is accepted, the parties must file a stipulation for dismissal with the court.

And Arizona’s A.R.S. § 12-1501(B) includes an explicit timing/good-faith instruction for defendant offers:

  • The defendant’s offer must be made in good faith and within the prescribed time frame (notably tied to the same “more than 30 days before trial” rule).

Because the statute has a strict timing element, DocketMath’s analyzer is most helpful when you can enter:

  • the scheduled trial start date, and
  • the proposed offer date, and
  • the amount offered and how that compares to expected trial outcomes.

Step-by-step example

Below is a concrete walkthrough. Adjust numbers to your case; the “moving parts” are what matter.

Scenario inputs (example)

Assume a civil case in Arizona with:

  • Trial begins: October 1, 2026
  • Offer date: August 15, 2026
  • Offered judgment amount: $75,000
  • Expected trial recovery (modeled): $90,000
  • Estimated taxable costs (if applicable in your inputs): $6,000
  • Estimated attorneys’ fees to be considered (if your tool workflow includes fee fields): $18,000

Step 1: Verify the timing under A.R.S. § 12-1501(A)

Under A.R.S. § 12-1501(A), the offer must be made “more than 30 days before the trial begins.”

  • Trial begins: Oct 1, 2026
  • 30-day cutoff: Sept 1, 2026 (30 days before)
  • Offer date: Aug 15, 2026

Because Aug 15 is more than 30 days before Oct 1, the offer timing passes the threshold under the statute’s timing condition.

Step 2: Check the defendant-good-faith framing (A.R.S. § 12-1501(B))

If you are the defendant and the offer is being offered by the defense, A.R.S. § 12-1501(B) requires the offer be made:

  • in good faith, and
  • within the prescribed time frame.

DocketMath can’t prove “good faith” for you, but it can help you document compliance by ensuring your entered offer date satisfies the timing rule. The “good faith” portion is a legal/factual assessment tied to the offer’s substance and context.

Warning: Timing compliance alone doesn’t guarantee statutory outcomes. Courts can scrutinize whether an offer was genuinely made in good faith, not as a token gesture.

Step 3: Model “accepted vs. rejected” results

Now compare the offer amount to the modeled judgment amount.

  • Offer: $75,000
  • Modeled outcome at trial: $90,000

Conceptually, if the offer is accepted, the case ends by stipulation of dismissal after acceptance (per A.R.S. § 12-1501(A)). If rejected and the matter proceeds to judgment, the statute’s cost/fee consequences can tilt depending on how the final judgment compares to the offer.

DocketMath’s analyzer typically helps by:

  • calculating differences between the offer amount and the likely judgment range, and
  • organizing the financial impact into scenario buckets.

Step 4: Review the output and interpret changes

When you adjust inputs, watch for these output shifts:

  • Increase the offer amount → closer to the expected judgment value → reduces the “gap” and may reduce downside risk if rejected.
  • Move the offer date closer to trial → the tool will flag timing risk if it violates the “more than 30 days” requirement in A.R.S. § 12-1501(A).
  • Increase estimated costs/fees (if your workflow includes them) → the cost/fee delta between scenarios grows.

In practice, the biggest “leverage” variable is the difference between:

  • offer amount, and
  • the judgment the parties realistically expect after trial.

Step 5: Document the reasoning before filing or responding

Before you finalize strategy, capture a short checklist in your file:

  • ✅ Offer date is > 30 days before trial (A.R.S. § 12-1501(A))
  • ✅ If defendant: offer must be within time frame and in good faith (A.R.S. § 12-1501(B))
  • ✅ Offer amount is entered consistently with how your case values damages and claims
  • ✅ Your “accepted” scenario assumes filing a stipulation for dismissal after acceptance (A.R.S. § 12-1501(A))

For convenience, jump directly to DocketMath’s calculator here:
/tools/offer-of-judgment-analyzer

Common scenarios

Offer-of-judgment analysis tends to come up in predictable litigation patterns. Below are frequent scenarios and how the calculator helps you think through them.

1) Defendant makes an offer early, then trial date is reset

  • If the trial date changes, a previously “timely” offer might become untimely relative to the new trial start date.
  • DocketMath helps you rerun the timing check quickly using the updated trial date.

Checklist:

2) Plaintiff rejects an offer that’s close to projected damages

Sometimes the dispute is less about the offer amount and more about risk tolerance.

What DocketMath shows:

  • how the offer vs. modeled judgment gap changes as you vary assumptions,
  • and how sensitive your results are to the expected recovery number.

Try it:

3) “Token” offers and good-faith concerns (defendant-side)

If the defense offers a number that doesn’t reflect plausible valuation, that can complicate the good faith requirement under A.R.S. § 12-1501(B).

DocketMath won’t determine whether a court finds good faith, but the tool encourages alignment between:

  • offer amount, and
  • realistic damages/defenses inputs you provide.

Pitfall:

Pitfall: An offer that’s mathematically “within time” but substantively detached from the case’s valuation may create vulnerability under the statute’s good-faith requirement for defendant offers (A.R.S. § 12-1501(B)).

4) Settlement discussions happen “late,” but parties still want the statute’s effects

The statute has a hard timing rule for offers: more than 30 days before trial begins (A.R.S. § 12-1501(A)).

If your timeline compresses, DocketMath becomes a quick diagnostic:

Tips for accuracy

To get meaningful outputs from DocketMath, focus on data hygiene and timing precision.

Timing accuracy (most critical)

Under A.R.S. § 12-1501(A), the offer must be made more than 30 days before the trial begins. Under A.R.S. § 12-1501(B), the defendant’s offer must be made in good faith and within that prescribed time frame.

Practical steps:

  • Use the actual trial start date (not an estimate), if you have it.
  • Re-run the timing check after any court scheduling updates.

Financial inputs: keep them consistent

If your analyzer includes fields for costs/fees, ensure your amounts reflect the type of financial impacts you expect to be relevant in your case’s post-judgment posture.

Good habits:

  • Use the same time period and assumptions across scenarios.
  • If you don’t know fees yet, run multiple versions (low / medium / high) to see how outcomes swing.

Document what you changed between runs

When you tweak one variable, write down what changed:

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