diff --git a/reasoning_gym/arithmetic/leg_counting.py b/reasoning_gym/arithmetic/leg_counting.py
new file mode 100644
index 00000000..8b25e98f
--- /dev/null
+++ b/reasoning_gym/arithmetic/leg_counting.py
@@ -0,0 +1,117 @@
+"""Leg counting task generator"""
+from dataclasses import dataclass
+from random import Random
+from typing import Dict, List, Optional, Tuple
+
+ANIMALS = {
+    "spider": 8,
+    "insect": 6,
+    "dog": 4,
+    "chicken": 2,
+    "snake": 0,
+    "cat": 4,
+    "bird": 2,
+    "cow": 4,
+    "ant": 6,
+    "scorpion": 8,
+    "human": 2,
+    "horse": 4,
+    "duck": 2,
+    "butterfly": 6,
+    "centipede": 100,
+}
+
+@dataclass
+class LegCountingConfig:
+    """Configuration for leg counting task generation"""
+    min_animals: int = 2        # Minimum number of animals in problem
+    max_animals: int = 5        # Maximum number of animals
+    max_instances: int = 3      # Maximum instances of each animal
+    seed: Optional[int] = None
+    size: int = 500            # Virtual dataset size
+
+    def validate(self):
+        """Validate configuration parameters"""
+        assert self.min_animals > 0, "min_animals must be positive"
+        assert self.max_animals >= self.min_animals, "max_animals must be >= min_animals"
+        assert self.max_instances > 0, "max_instances must be positive"
+
+
+class LegCountingDataset:
+    """Generates leg counting arithmetic tasks"""
+
+    def __init__(self, config: LegCountingConfig):
+        self.config = config
+        self.config.validate()
+        self.seed = config.seed if config.seed is not None else Random().randint(0, 2**32)
+
+    def __len__(self) -> int:
+        return self.config.size
+
+    def __iter__(self):
+        self._current_idx = 0
+        return self
+
+    def __next__(self):
+        if self._current_idx >= self.config.size:
+            raise StopIteration
+        item = self[self._current_idx]
+        self._current_idx += 1
+        return item
+
+    def _generate_animals(self, rng: Random) -> Dict[str, int]:
+        """Generate a random set of animals and their counts"""
+        num_types = rng.randint(self.config.min_animals, self.config.max_animals)
+        animals = {}
+        
+        # Select random animals
+        selected_animals = rng.sample(list(ANIMALS.keys()), num_types)
+        for animal in selected_animals:
+            count = rng.randint(1, self.config.max_instances)
+            animals[animal] = count
+            
+        return animals
+
+    def __getitem__(self, idx: int) -> dict:
+        """Generate a single leg counting task"""
+        rng = Random(self.seed + idx)
+        
+        # Generate random animals and their counts
+        animals = self._generate_animals(rng)
+        
+        # Calculate total legs
+        total_legs = sum(count * ANIMALS[animal] for animal, count in animals.items())
+        
+        # Format animal counts for question
+        animal_list = []
+        for animal, count in animals.items():
+            animal_list.append(f"{count} {animal}{'s' if count > 1 else ''}")
+            
+        question = "How many legs are there in total if you have " + ", ".join(animal_list) + "?"
+        
+        return {
+            "question": question,
+            "answer": str(total_legs),
+            "metadata": {
+                "animals": animals,
+                "total_legs": total_legs
+            }
+        }
+
+
+def leg_counting_dataset(
+    min_animals: int = 2,
+    max_animals: int = 5,
+    max_instances: int = 3,
+    seed: Optional[int] = None,
+    size: int = 500,
+) -> LegCountingDataset:
+    """Create a LegCountingDataset with the given configuration."""
+    config = LegCountingConfig(
+        min_animals=min_animals,
+        max_animals=max_animals,
+        max_instances=max_instances,
+        seed=seed,
+        size=size,
+    )
+    return LegCountingDataset(config)