diff --git a/stat/correlation.py b/stat/correlation.py
new file mode 100644
index 0000000..dc81132
--- /dev/null
+++ b/stat/correlation.py
@@ -0,0 +1,144 @@
+# File: correlation.py
+# Copyright (C) 2026 Erick Ahmed
+# SPDX-License-Identifier: AGPL-3.0-or-later
+
+import argparse
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+import plotly.graph_objects as go
+
+from utils.extractor import load_data
+
+
+def _to_int(x):
+    """Convert a hex string or integer to int, returning NaN on failure."""
+    if isinstance(x, (int, np.integer)):
+        return int(x)
+    if isinstance(x, str):
+        try:
+            return int(x, 16)
+        except ValueError:
+            return np.nan
+    return np.nan
+
+
+def calculate_correlation(df: pd.DataFrame, method: str, target_id: str | None = None) -> pd.DataFrame:
+    """Calculates inter-byte correlation grouped by identifier."""
+    byte_cols = [f"b{i}" for i in range(8)]
+    available_cols = [col for col in byte_cols if col in df.columns]
+
+    if not available_cols:
+        raise ValueError("No byte columns (b0-b7) found in the DataFrame")
+
+    df_bytes = df[["Identifier"] + available_cols].copy()
+    for col in available_cols:
+        df_bytes[col] = df_bytes[col].apply(_to_int)
+
+    if target_id:
+        group = df_bytes[df_bytes["Identifier"] == target_id]
+        if group.empty:
+            raise ValueError(f"Identifier '{target_id}' not found in data")
+        return group[available_cols].corr(method=method).fillna(0.0)
+
+    def max_abs_corr(group: pd.DataFrame) -> pd.Series:
+        corr_arr = np.abs(group.corr(method=method).to_numpy().copy())
+        np.fill_diagonal(corr_arr, 0.0)
+        return pd.Series(corr_arr.max(axis=0), index=group.columns).fillna(0.0)
+
+    return df_bytes.groupby("Identifier")[available_cols].apply(max_abs_corr)
+
+
+def plot_correlation_heatmap(corr_df: pd.DataFrame, target_id: str | None, title: str) -> go.Figure:
+    """Generates an interactive heatmap of inter-byte correlation."""
+    is_8x8 = target_id is not None
+
+    if is_8x8:
+        x = corr_df.columns.tolist()
+        y = corr_df.index.tolist()
+        z = corr_df.values
+        z_min, z_max = -1.0, 1.0
+        colorscale = [
+            [0.0, "#2c7bb6"], [0.25, "#abd9e9"], [0.5, "#ffffff"],
+            [0.75, "#fdae61"], [1.0, "#d7191c"]
+        ]
+        hover_template = "<b>%{y}</b> vs <b>%{x}</b><br>Correlation: %{z:.2f}<extra></extra>"
+    else:
+        x = corr_df.columns.tolist()
+        y = corr_df.index.tolist()
+        z = corr_df.values
+        z_min, z_max = 0.0, 1.0
+        colorscale = [
+            [0.0, "#ffffff"], [0.2, "#fff5f0"], [0.4, "#fecc5c"],
+            [0.6, "#fd8d3c"], [0.8, "#e31a1c"], [1.0, "#800026"]
+        ]
+        hover_template = "<b>%{y}</b><br>Byte %{x} max correlation: %{z:.2f}<extra></extra>"
+
+    fig = go.Figure(
+        data=go.Heatmap(
+            z=z, x=x, y=y,
+            zmin=z_min, zmax=z_max,
+            colorscale=colorscale,
+            xgap=3, ygap=3,
+            text=np.round(z, 2),
+            texttemplate="%{text}",
+            textfont={"size": 11, "color": "#2a2a2a", "family": "Segoe UI, Arial, sans-serif"},
+            hoverongaps=False,
+            hovertemplate=hover_template,
+            colorbar=dict(
+                title=dict(text="Correlation", side="top", font=dict(size=13, color="#1a1a1a")),
+                orientation="h", thickness=15, len=0.35,
+                x=1.0, xanchor="right", y=1.02, yanchor="bottom",
+                tickfont=dict(size=11, color="#2a2a2a"),
+                tickformat=".1f", outlinewidth=0.5, outlinecolor="#cccccc",
+            ),
+        )
+    )
+
+    fig.update_layout(
+        title=dict(text=title, font=dict(size=20, color="#1a1a1a"), x=0.5, xanchor="center", pad=dict(b=20)),
+        height=max(600, len(y) * 28 + 150) if not is_8x8 else 600,
+        autosize=True,
+        template="plotly_white",
+        xaxis=dict(
+            title=dict(text="Byte Position", font=dict(size=13, color="#1a1a1a")),
+            side="top" if not is_8x8 else "bottom",
+            dtick=1, showgrid=False, linecolor="#bdbdbd",
+            tickfont=dict(size=12, color="#2a2a2a"), ticks="outside", ticklen=4, tickcolor="#cccccc",
+        ),
+        yaxis=dict(
+            title=dict(text="PGN or CAN ID" if not is_8x8 else "Byte Position", font=dict(size=13, color="#1a1a1a")),
+            autorange="reversed", showgrid=False, linecolor="#bdbdbd",
+            tickfont=dict(size=12, color="#2a2a2a"), ticks="outside", ticklen=4, tickcolor="#cccccc", automargin=True,
+        ),
+        font=dict(family="Segoe UI, Arial, sans-serif", size=12, color="#2a2a2a"),
+        hoverlabel=dict(bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor="#cccccc"),
+        margin=dict(l=200, r=40, t=120, b=60),
+    )
+    return fig
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(description="Analyze CAN bus inter-byte correlation")
+    parser.add_argument("method", choices=["pearson", "spearman"], help="Correlation method to use")
+    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
+    parser.add_argument("output", type=Path, nargs="?", default=Path("correlation_report.html"), help="Path to the output HTML report")
+    parser.add_argument("title", nargs="?", default="CAN Bus Inter-Byte Correlation", help="Title for the HTML report")
+    parser.add_argument("--identifier", type=str, default=None, help="Specific PGN/CAN ID to analyze (e.g., 'PGN: 65331'). If omitted, shows max correlation per byte for all IDs.")
+    args = parser.parse_args()
+
+    df = load_data(args.input)
+    corr_df = calculate_correlation(df, method=args.method, target_id=args.identifier)
+
+    display_title = f"{args.title} ({args.identifier})" if args.identifier else args.title
+    fig = plot_correlation_heatmap(corr_df, target_id=args.identifier, title=display_title)
+
+    config = {
+        "responsive": True,
+        "displaylogo": False,
+        "scrollZoom": True,
+        "modeBarButtonsToAdd": ["toggleSpikelines"],
+        "toImageButtonOptions": {"format": "png", "scale": 2},
+    }
+    fig.write_html(str(args.output), include_plotlyjs="cdn", config=config)
diff --git a/stat/utils/extractor.py b/stat/utils/extractor.py
index 8cdd07e..807835b 100644
--- a/stat/utils/extractor.py
+++ b/stat/utils/extractor.py
@@ -1,11 +1,20 @@
-# File: extractor.py
-# Copyright (C) 2026 Erick Ahmed
-# SPDX-License-Identifier: AGPL-3.0-or-later
-
 import json
 from pathlib import Path
+
+import numpy as np
 import pandas as pd
 
+def to_int(x):
+    """Convert a hex string or integer to int, returning NaN on failure."""
+    if isinstance(x, (int, np.integer)):
+        return int(x)
+    if isinstance(x, str):
+        try:
+            return int(x, 16)
+        except ValueError:
+            return np.nan
+    return np.nan
+
 def extract_id(row: pd.Series) -> str:
     """Extracts PGN from metadata or falls back to CAN ID."""
     meta = row.get('j1939_metadata')