How to estimate car accident settlements in California

Direct answer

In California, you can estimate a car accident settlement by modeling how fault is allocated among parties and then applying California’s economic vs. non-economic damages allocation structure in Cal. Civ. Code § 1431.2, as discussed in Li v. Yellow Cab Co., 13 Cal. 3d 804 (1975). Practically, you do this in DocketMath using the /tools/damages-allocation calculator.

This is a calculation framework, not legal advice. Your inputs—especially the fault allocation you think a factfinder could find and the evidence supporting economic losses—can swing the settlement range even when you use the same method.

What you need to know

California’s damages allocation approach centers on two ideas: (1) comparative fault allocation and (2) how the statute treats economic vs. non-economic damages.

1) Fault allocation is the starting point (and it must be complete)

In your DocketMath run, enter a fault percentage per party so the allocations sum to 100% (this matches the “trier of fact” allocation concept used for comparative responsibility modeling).

A practical way to make settlement estimates more realistic is to create more than one fault scenario, such as:

• Liability set A: what the evidence most strongly supports now
• Liability set B: a more conservative (or plaintiff-favorable/defense-favorable) scenario

You’ll then compare how the outputs change across scenarios.

2) Economic vs. non-economic damages are treated differently

Under Cal. Civ. Code § 1431.2(b), the statute distinguishes between:

• Economic damages (treated under the statute as joint and several). These are objectively verifiable monetary losses, including (as listed in § 1431.2(b)(1)):
  medical expenses, loss of earnings, burial costs, loss of use of property, costs of repair or replacement, costs of obtaining substitute domestic services, loss of employment, and loss of business or employment opportunities.

• Non-economic damages (treated as several only). These are subjective, non-monetary losses, including (as listed in § 1431.2(b)(2)):
  pain and suffering, inconvenience, mental suffering, emotional distress, loss of society and companionship, loss of consortium, injury to reputation, and humiliation.

3) Case law supports the allocation-thinking behind the model

Li v. Yellow Cab Co., 13 Cal. 3d 804 (1975) is a key California decision frequently used to understand how California’s tort framework handles allocation concepts that matter for distributing responsibility through the damages analysis.

4) DocketMath turns your inputs into allocation-aware outputs

In /tools/damages-allocation, you typically:

• enter fault allocations (sum to 100%)
• enter economic damages totals
• enter non-economic damages totals
  and then use the allocation-aware outputs to compare settlement-range scenarios.

Step-by-step

Use this workflow to estimate a settlement range using DocketMath and California’s § 1431.2 structure.

Step 1: Build a fault allocation set in DocketMath (must total 100%)

In DocketMath’s /tools/damages-allocation:

1. Add each party you’ll allocate to.
2. Enter fault percentages for each party.
3. Confirm the percentages sum to 100%.

Checklist:

• Fault percentages add up to 100%
• The parties included match across the scenarios you compare
• You can point to evidence supporting each percentage (e.g., eyewitness/traffic facts, injury timing relevance to causation)

Step 2: Create an economic damages total from proof you can support

Create a single economic damages input for your run using the categories listed in § 1431.2(b)(1) (examples: medical expenses and documented treatment, loss of earnings, repair/replacement costs, and other objectively verifiable monetary losses).

Checklist:

• The amounts you include align with objectively verifiable monetary categories
• You’re not mixing in non-economic items (pain/suffering) into this bucket

Step 3: Create a non-economic damages total for your run

Create a single non-economic damages input aligned with § 1431.2(b)(2) (examples: pain and suffering, emotional distress, loss of society/companionship, and related non-monetary categories).

Practical tip: If you have uncertainty about the valuation, consider running multiple non-economic values (for example, a low/medium/high approach) while keeping fault and economic damages constant. This helps isolate what drives the output most.

Step 4: Run the calculator for baseline and sensitivity scenarios

Run at least two scenarios:

• Baseline: your best estimate of fault allocation plus your best estimate of economic and non-economic totals
• Sensitivity: change fault allocation meaningfully (but plausibly) and re-run

Then compare outputs to see:

• how much economic damages remain effectively “reachable” under your allocation assumptions, and
• how non-economic damages are handled under the statute’s several-only treatment.

Step 5: Translate allocated outputs into a settlement-range mindset

Once you have allocation-aware results, use them to support settlement-range thinking—not by treating the math as the final word, but by organizing your negotiating position around:

• the strength/weakness of the evidence behind each fault percentage
• how provable your economic damages inputs are
• where your non-economic valuation assumptions sit

Key statutes and citations

• Cal. Civ. Code § 1431.2 — provides the economic vs. non-economic allocation structure used in California tort damages allocation (including the joint and several treatment of economic damages and several-only treatment of non-economic damages).
  Source URL: https://leginfo.legislature.ca.gov/faces/codes_displaySection.xhtml?lawCode=CIV&sectionNum=1431.2.

• Li v. Yellow Cab Co., 13 Cal. 3d 804 (1975) — a key California tort decision discussing allocation concepts relevant to how damages allocation is analyzed.

Common pitfalls

Pitfall 1: Treating non-economic damages like economic damages in your model logic

Non-economic damages fall under § 1431.2(b)(2) and are treated as several only. If you model them as though they behave like the economic bucket, your estimate can be materially off.

Pitfall 2: Fault percentages that don’t sum to 100%

If your allocation set doesn’t total 100%, the run stops reflecting a complete allocation framework.

Pitfall 3: Over-including items inside the economic bucket

Economic damages under § 1431.2(b)(1) are objectively verifiable monetary losses. If you include items that are really non-economic (or not supportable as monetary losses), your economic input becomes less defensible.

Pitfall 4: Running only one scenario

A single scenario can look confident but hides uncertainty. Doing at least baseline + one sensitivity run is usually more informative for settlement-range modeling.

Run the numbers

Here’s a practical modeling checklist you can use with DocketMath at /tools/damages-allocation.

Input checklist (what you’ll enter)

• Fault allocation percentages per party (sum to 100%)
• Economic damages total aligned to § 1431.2(b)(1)
• Non-economic damages total aligned to § 1431.2(b)(2)

Output interpretation checklist (what you’ll review)

• Economic outputs reflect the statute’s allocation treatment for economic damages
• Non-economic outputs reflect the statute’s several only treatment for non-economic damages
• Baseline vs. sensitivity shows a range that matches your confidence in fault and damages evidence

Scenario table (copy/paste template)

Related reading

• How to calculate Damages Allocation in Philippines — Full how-to guide with jurisdiction-specific rules
• Worked example: Damages Allocation in Philippines — Worked example with real statute citations
• Inputs you need for Damages Allocation in Philippines — Input checklist with sourcing guidance