diff --git a/src/components/side_panel/chart/chart_with_axis/design_panel.ts b/src/components/side_panel/chart/chart_with_axis/design_panel.ts
index 7250b36aac..c6588ce0dc 100644
--- a/src/components/side_panel/chart/chart_with_axis/design_panel.ts
+++ b/src/components/side_panel/chart/chart_with_axis/design_panel.ts
@@ -195,7 +195,7 @@ export class ChartWithAxisDesignPanel<P extends Props = Props> extends Component
       case "polynomial":
         config = {
           type: "polynomial",
-          order: type === "linear" ? 1 : 2,
+          order: type === "linear" ? 1 : this.getMaxPolynomialDegree(),
         };
         break;
       case "exponential":
diff --git a/src/helpers/figures/charts/chart_common.ts b/src/helpers/figures/charts/chart_common.ts
index 1678e18ceb..7ed05dca34 100644
--- a/src/helpers/figures/charts/chart_common.ts
+++ b/src/helpers/figures/charts/chart_common.ts
@@ -535,41 +535,48 @@ export function interpolateData(
   const labelRange = labelMax - labelMin;
   const normalizedLabels = labels.map((v) => (v - labelMin) / labelRange);
   const normalizedNewLabels = newLabels.map((v) => (v - labelMin) / labelRange);
-  switch (config.type) {
-    case "polynomial": {
-      const order = config.order ?? 2;
-      if (order === 1) {
-        return predictLinearValues([values], [normalizedLabels], [normalizedNewLabels], true)[0];
+  try {
+    switch (config.type) {
+      case "polynomial": {
+        const order = config.order;
+        if (!order) {
+          return Array.from({ length: newLabels.length }, () => NaN);
+        }
+        if (order === 1) {
+          return predictLinearValues([values], [normalizedLabels], [normalizedNewLabels], true)[0];
+        }
+        const coeffs = polynomialRegression(values, normalizedLabels, order, true).flat();
+        return normalizedNewLabels.map((v) => evaluatePolynomial(coeffs, v, order));
       }
-      const coeffs = polynomialRegression(values, normalizedLabels, order, true).flat();
-      return normalizedNewLabels.map((v) => evaluatePolynomial(coeffs, v, order));
-    }
-    case "exponential": {
-      const positiveLogValues: number[] = [];
-      const filteredLabels: number[] = [];
-      for (let i = 0; i < values.length; i++) {
-        if (values[i] > 0) {
-          positiveLogValues.push(Math.log(values[i]));
-          filteredLabels.push(normalizedLabels[i]);
+      case "exponential": {
+        const positiveLogValues: number[] = [];
+        const filteredLabels: number[] = [];
+        for (let i = 0; i < values.length; i++) {
+          if (values[i] > 0) {
+            positiveLogValues.push(Math.log(values[i]));
+            filteredLabels.push(normalizedLabels[i]);
+          }
+        }
+        if (!filteredLabels.length) {
+          return Array.from({ length: newLabels.length }, () => NaN);
         }
+        return expM(
+          predictLinearValues([positiveLogValues], [filteredLabels], [normalizedNewLabels], true)
+        )[0];
       }
-      if (!filteredLabels.length) {
-        return [];
+      case "logarithmic": {
+        return predictLinearValues(
+          [values],
+          logM([normalizedLabels]),
+          logM([normalizedNewLabels]),
+          true
+        )[0];
       }
-      return expM(
-        predictLinearValues([positiveLogValues], [filteredLabels], [normalizedNewLabels], true)
-      )[0];
-    }
-    case "logarithmic": {
-      return predictLinearValues(
-        [values],
-        logM([normalizedLabels]),
-        logM([normalizedNewLabels]),
-        true
-      )[0];
+      default:
+        return [];
     }
-    default:
-      return [];
+  } catch (e) {
+    return Array.from({ length: newLabels.length }, () => NaN);
   }
 }
 
diff --git a/tests/figures/chart/chart_plugin.test.ts b/tests/figures/chart/chart_plugin.test.ts
index e484be2cb6..486a5683a7 100644
--- a/tests/figures/chart/chart_plugin.test.ts
+++ b/tests/figures/chart/chart_plugin.test.ts
@@ -3209,6 +3209,20 @@ describe("trending line", () => {
     }
   });
 
+  test("non-invertible matrix doesn't throw error", () => {
+    // prettier-ignore
+    setGrid(model, {
+      A1: "label",
+      A2: "0",
+      A3: "1",
+    });
+    updateChart(model, "1", {
+      dataSets: [{ dataRange: "A1:A3", trend: { display: true, type: "polynomial", order: 2 } }],
+    });
+    const runtime = model.getters.getChartRuntime("1") as LineChartRuntime;
+    expect(runtime.chartJsConfig.data.datasets[1].data.every((x) => isNaN(Number(x)))).toBeTruthy();
+  });
+
   test("trend line works with real date values as labels", () => {
     setGrid(model, {
       B1: "1",