Leggett & Platt (LEG) EBITDA (2009 - 2026)
Leggett & Platt (LEG) posted EBITDA of $101.5 million for Q2 2026, down 2.0% from $103.6 million a year earlier but up 37.3% from the prior quarter.
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Analysis
Leggett & Platt (LEG) EBITDA (2009 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EBITDA at Leggett & Platt was $351.3 million, down 11.2% year-over-year; for FY2025, it came in at $378.2 million, up 0.5% from FY2024.
- Annual EBITDA shows a five-year compound annual growth rate of -10.8% (FY2020 to FY2025).
- In prior years, Leggett & Platt's EBITDA was $376.3 million in FY2024 (-33.8%), $568.3 million in FY2023 (-22.1%), $729.3 million in FY2022 (-9.2%) and $803.5 million in FY2021 (+20.1%).
- Quarterly EBITDA has run from a low of $73.9 million in Q1 2026 to a high of $212.3 million in Q4 2021 over five years.
- On a year-over-year basis, EBITDA has declined in each of the last four quarters, with an average decline of 10.1% over the last eight quarters.
- The strongest year-over-year quarter for EBITDA in the past five years was Q2 2025, with growth of 18.1%; the weakest was Q2 2024, with a decline of 39.7%.
- According to Business Quant data, EBITDA for the three prior quarters was $73.9 million (Q1 2026), $77.7 million (Q4 2025) and $98.2 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Caterpillar | 372.79 Bn | 344.49 Bn | 7.76 Bn | 4.91 Bn |
| 2 | Amphenol | 207.98 Bn | 202.68 Bn | 3.55 Bn | 2.93 Bn |
| 3 | Deere | 181.02 Bn | 189.78 Bn | 4.66 Bn | 2.46 Bn |
| 4 | Eaton | 166.86 Bn | 164.09 Bn | 2.86 Bn | 1.79 Bn |
| 5 | Parker-Hannifin | 120.45 Bn | 118.58 Bn | 2.25 Bn | 1.61 Bn |
| 6 | Vertiv Holdings | 92.94 Bn | 83.56 Bn | 1.23 Bn | 753.70 Mn |
| 7 | Emerson Electric | 86.56 Bn | 79.32 Bn | 2.66 Bn | 1.69 Bn |
| 8 | 3M | 84.72 Bn | 66.18 Bn | 2.68 Bn | 1.32 Bn |
| 9 | Illinois Tool Works | 73.32 Bn | 69.88 Bn | 1.90 Bn | 1.25 Bn |
| 10 | Leggett & Platt | 1.26 Bn | -847.28 Mn | 203.20 Mn | 101.50 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 101.50 Mn |
| Mar 31, 2026 | 73.90 Mn |
| Dec 31, 2025 | 77.70 Mn |
| Sep 30, 2025 | 98.20 Mn |
| Jun 30, 2025 | 103.60 Mn |
| Mar 31, 2025 | 98.00 Mn |
| Dec 31, 2024 | 85.30 Mn |
| Sep 30, 2024 | 108.70 Mn |
| Jun 30, 2024 | 87.70 Mn |
| Mar 31, 2024 | 93.40 Mn |
| Dec 31, 2023 | 123.50 Mn |
| Sep 30, 2023 | 150.10 Mn |
| Jun 30, 2023 | 145.50 Mn |
| Mar 31, 2023 | 148.00 Mn |
| Dec 31, 2022 | 146.30 Mn |
| Sep 30, 2022 | 173.60 Mn |
| Jun 30, 2022 | 207.20 Mn |
| Mar 31, 2022 | 201.30 Mn |
| Dec 31, 2021 | 212.30 Mn |
| Sep 30, 2021 | 199.10 Mn |
API Access
Leggett & Platt EBITDA API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=ebitda&ticker=LEG&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "LEG", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=LEG&period=max&api_key=YOUR_API_KEY");
const data = await res.json();