diff --git a/pymc3/sampling.py b/pymc3/sampling.py
index 0b7eac9e23..2e4963e867 100644
--- a/pymc3/sampling.py
+++ b/pymc3/sampling.py
@@ -318,7 +318,7 @@ def _soft_update(a, b):
     a.update({k: v for k, v in b.items() if k not in a})
 
 
-def sample_ppc(trace, samples=None, model=None, vars=None, size=None, random_seed=None):
+def sample_ppc(trace, samples=None, model=None, vars=None, size=None, random_seed=None, progressbar=True):
     """Generate posterior predictive samples from a model given a trace.
 
     Parameters
@@ -353,8 +353,13 @@ def sample_ppc(trace, samples=None, model=None, vars=None, size=None, random_see
 
     seed(random_seed)
 
+    if progressbar:
+        indices = tqdm(randint(0, len(trace), samples), total=samples)
+    else:
+        indices = randint(0, len(trace), samples)
+
     ppc = defaultdict(list)
-    for idx in randint(0, len(trace), samples):
+    for idx in indices:
         param = trace[idx]
         for var in vars:
             ppc[var.name].append(var.distribution.random(point=param,
diff --git a/pymc3/variational/advi.py b/pymc3/variational/advi.py
index 2edd409acb..2e3795754f 100644
--- a/pymc3/variational/advi.py
+++ b/pymc3/variational/advi.py
@@ -12,6 +12,8 @@
 import pymc3 as pm
 from pymc3.backends.base import MultiTrace
 
+from tqdm import trange
+
 __all__ = ['advi', 'sample_vp']
 
 ADVIFit = namedtuple('ADVIFit', 'means, stds, elbo_vals')
@@ -272,7 +274,7 @@ def optimizer(loss, param):
 
 def sample_vp(
         vparams, draws=1000, model=None, local_RVs=None, random_seed=None,
-        hide_transformed=True):
+        hide_transformed=True, progressbar=True):
     """Draw samples from variational posterior.
 
     Parameters
@@ -344,7 +346,9 @@ def sample_vp(
     trace = pm.sampling.NDArray(model=model, vars=vars_sampled)
     trace.setup(draws=draws, chain=0)
 
-    for i in range(draws):
+    range_ = trange(draws) if progressbar else range(draws)
+
+    for i in range_:
         # 'point' is like {'var1': np.array(0.1), 'var2': np.array(0.2), ...}
         point = {varname: value for varname, value in zip(varnames, f())}
         trace.record(point)