diff --git a/README.Rmd b/README.Rmd
index c20f6aa..97bb33b 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -22,7 +22,7 @@ knitr::opts_chunk$set(
 
 `saeczi` is an R package that implements a small area estimator that uses a two-stage modeling approach for zero-inflated response variables. In particular, we are working with variables that follow a semi-continuous distribution with a mixture of zeroes and positive continuously distributed values. An example can be seen below.
 
-![](figs/README-zi-plot-1.png)
+![](figs/README-zi-plot-1.png){width = 70%}
 
 `saeczi` first fits a linear mixed model to the non-zero portion of the response and then a generalized linear mixed model with binomial response to classify the probability of zero for a given data point. In estimation these models are each applied to new data points and combined to compute a final prediction.
 
@@ -66,6 +66,9 @@ result <- saeczi(samp_dat = samp,
                  B = 1000L)
 ```
 
+
+#### Return 
+
 The function returns the following objects:
 
 | Name            | Description                                                               |
@@ -84,5 +87,20 @@ result$res |> head()
 
 ### Parallelization
 
+`saeczi` supports parallelization through the `future` package to speed up the bootstrapping process, but requires a small amount of additional work on the part of the user. It is not enough just to specify `parallel = TRUE` in the function signature as a `future::plan` must also be specified. 
+
+Below is an example that uses multisession' future resolution with 6 threads:
+
+```{r, eval = FALSE}
+future::plan("multisession", workers = 6)
+result_par <- saeczi(samp_dat = samp,
+                     pop_dat = pop, 
+                     lin_formula =  DRYBIO_AG_TPA_live_ADJ ~ tcc16 + elev,
+                     log_formula = DRYBIO_AG_TPA_live_ADJ ~ tcc16,
+                     domain_level = "COUNTYFIPS",
+                     mse_est = TRUE,
+                     parallel = TRUE,
+                     B = 1000L)
+```
 
 
diff --git a/README.md b/README.md
index ae64f87..b08043f 100644
--- a/README.md
+++ b/README.md
@@ -19,7 +19,7 @@ In particular, we are working with variables that follow a
 semi-continuous distribution with a mixture of zeroes and positive
 continuously distributed values. An example can be seen below.
 
-![](figs/README-zi-plot-1.png)
+![](figs/README-zi-plot-1.png){width = 70%}
 
 `saeczi` first fits a linear mixed model to the non-zero portion of the
 response and then a generalized linear mixed model with binomial
@@ -80,6 +80,8 @@ result <- saeczi(samp_dat = samp,
                  B = 1000L)
 ```
 
+#### Return
+
 The function returns the following objects:
 
 | Name            | Description                                                               |
@@ -95,13 +97,34 @@ few rows of the results:
 
 ``` r
 result$res |> head()
-#>   COUNTYFIPS      mse       est
-#> 1      41001 216.3487  14.57288
-#> 2      41003 144.6466 103.33016
-#> 3      41005 276.4164  86.08616
-#> 4      41007 584.4503  78.79615
-#> 5      41009 169.2617  73.98920
-#> 6      41011 656.6422  90.44174
+#>   COUNTYFIPS         mse       est
+#> 1      41001   524.33803  14.57288
+#> 2      41003  1176.47914 103.33016
+#> 3      41005 18891.79642  86.08616
+#> 4      41007    27.43582  78.79615
+#> 5      41009  4674.77845  73.98920
+#> 6      41011    14.29977  90.44174
 ```
 
 ### Parallelization
+
+`saeczi` supports parallelization through the `future` package to speed
+up the bootstrapping process, but requires a small amount of additional
+work on the part of the user. It is not enough just to specify
+`parallel = TRUE` in the function signature as a `future::plan` must
+also be specified.
+
+Below is an example that uses multisession’ future resolution with 6
+threads:
+
+``` r
+future::plan("multisession", workers = 6)
+result_par <- saeczi(samp_dat = samp,
+                     pop_dat = pop, 
+                     lin_formula =  DRYBIO_AG_TPA_live_ADJ ~ tcc16 + elev,
+                     log_formula = DRYBIO_AG_TPA_live_ADJ ~ tcc16,
+                     domain_level = "COUNTYFIPS",
+                     mse_est = TRUE,
+                     parallel = TRUE,
+                     B = 1000L)
+```